Add README with file type guidelines and snake_case naming rule; update .gitignore typo

proj_level_reading/Requirement_Analysis/FRs-Database/FR-Engineer-DB .csv

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+ComponentName,ReqID,ReqName,IsOptional,UserProfileCode,Sys/Act,PreCondition,PostCondition,VerboseDescription,Engineer
+Prescription Parser / WebML Module,ULTS-Prescription Parser / WebML Module-FR-4,PARSE clinical text on-device,No,UP6,System,[The physical therapist opens the camera scanner within the PWA and captures the text-based prescription],"[The targeted joint zone, therapy modality, and frequency are extracted locally, and any structural contraindication warnings are displayed]","ULTS-Prescription Parser / WebML Module-FR-4: As an [Physical Therapist], provide that [The physical therapist opens the camera scanner within the PWA and captures the text-based prescription], the [System] shall PARSE clinical text on-device, ensuring that [The targeted joint zone, therapy modality, and frequency are extracted locally, and any structural contraindication warnings are displayed]",Đạt Trần Tiến (Daves Tran)
+3D Mapping / Visualization Engine,ULTS-3D Mapping / Visualization Engine-FR-5,MAP spatial coordinates to visual models,No,UP6,System,[Abstract text tokens are successfully parsed from the prescription.],[A dynamic visual guide—rendered via WebGL or a zero-GPU CPU-bound 2D image sequence based on device capabilities—with an SVG vector highlight over the target tissue area is displayed.],"ULTS-3D Mapping / Visualization Engine-FR-5: As an [Physical Therapist], provide that [Abstract text tokens are successfully parsed from the prescription.], the [System] shall MAP spatial coordinates to visual models, ensuring that [A dynamic visual guide—rendered via WebGL or a zero-GPU CPU-bound 2D image sequence based on device capabilities—with an SVG vector highlight over the target tissue area is displayed.]",Đạt Trần Tiến (Daves Tran)
+Kinetic Overlay Module,ULTS-Kinetic Overlay Module-FR-6,RENDER muscle depth cross-sections,No,UP6,System,[The physical therapist activates the Kinetic Overlay Toggle within the canvas view],[Lightweight HTML SVG paths detailing muscle cross-sections and 1 cm to 5 cm depth color-coding are dynamically appended over the target treatment viewport],"ULTS-Kinetic Overlay Module-FR-6: As an [Physical Therapist], provide that [The physical therapist activates the Kinetic Overlay Toggle within the canvas view], the [System] shall RENDER muscle depth cross-sections, ensuring that [Lightweight HTML SVG paths detailing muscle cross-sections and 1 cm to 5 cm depth color-coding are dynamically appended over the target treatment viewport]",Đạt Trần Tiến (Daves Tran)
+Progress Tracking Module,ULTS-Progress Tracking Module-FR-7,LOG kinetic progress pins,No,UP6,System,[The physical therapist taps the screen workspace layer within the distinct Kinetic Tracking Channel.],"[Localized metrics including Range of Motion, 1-10 pain indices, and tissue behavior are serialized and pushed to the physician's tracking panel without mutating the primary medical file.]","ULTS-Progress Tracking Module-FR-7: As an [Physical Therapist], provide that [The physical therapist taps the screen workspace layer within the distinct Kinetic Tracking Channel.], the [System] shall LOG kinetic progress pins, ensuring that [Localized metrics including Range of Motion, 1-10 pain indices, and tissue behavior are serialized and pushed to the physician's tracking panel without mutating the primary medical file.]",Đạt Trần Tiến (Daves Tran)
+Patient Education Module,ULTS-Patient Education Module-FR-8,DEMONSTRATE joint mechanics dynamically,No,UP6,System,[The physical therapist moves the HTML Range-of-Motion slider within the Patient Demonstration Mode split layout.],"[A cached array of 2D illustrations seamlessly cycles using 0% GPU power to visually indicate joint flexion, extension, and soft-tissue impingement.]","ULTS-Patient Education Module-FR-8: As an [Physical Therapist], provide that [The physical therapist moves the HTML Range-of-Motion slider within the Patient Demonstration Mode split layout.], the [System] shall DEMONSTRATE joint mechanics dynamically, ensuring that [A cached array of 2D illustrations seamlessly cycles using 0% GPU power to visually indicate joint flexion, extension, and soft-tissue impingement.]",Đạt Trần Tiến (Daves Tran)
+DICOM Viewer / Annotation Module,ULTS-DICOM Viewer / Annotation Module-FR-9,RENDER haptic-assisted edge-snapping magnifier,No,UP7,System,[The clinician activates the annotation tool and drags the crosshairs near a high-contrast bone boundary on the multi-touch viewport.],"[A high-magnification lens appears 150px vertically above the touch point, the crosshairs automatically snap to the nearest boundary, and a localized native haptic pulse is triggered.]","ULTS-DICOM Viewer / Annotation Module-FR-9: As an [Rheumatologist & Orthopedic Surgeon], provide that [The clinician activates the annotation tool and drags the crosshairs near a high-contrast bone boundary on the multi-touch viewport.], the [System] shall RENDER haptic-assisted edge-snapping magnifier, ensuring that [A high-magnification lens appears 150px vertically above the touch point, the crosshairs automatically snap to the nearest boundary, and a localized native haptic pulse is triggered.]",Đạt Trần Tiến (Daves Tran)
+Asynchronous Communication Engine,ULTS-Asynchronous Communication Engine-FR-10,RECORD asynchronous voice and canvas telemetry (Session Recording & Replay),No,UP7,System,[The sending clinician records audio while navigating the viewport and drawing vectors on the case file workspace.],"[The microphone input and viewport coordinate state changes (X, Y positions, zoom, panning) are compiled into a serialized JSON timeline file for synchronized, threaded playback.]","ULTS-Asynchronous Communication Engine-FR-10: As an [Rheumatologist & Orthopedic Surgeon], provide that [The sending clinician records audio while navigating the viewport and drawing vectors on the case file workspace.], the [System] shall RECORD asynchronous voice and canvas telemetry (Session Recording & Replay), ensuring that [The microphone input and viewport coordinate state changes (X, Y positions, zoom, panning) are compiled into a serialized JSON timeline file for synchronized, threaded playback.]",Đạt Trần Tiến (Daves Tran)
+User Interface / Push Notifications,ULTS-User Interface / Push Notifications-FR-11,DISPLAY progressive disclosure sheets and native alerts,No,UP7,System,[A case update occurs or the clinician interacts with the clinical data layout over the active DICOM canvas.],"[A deep-linked native OS push alert is sent, and clinical telemetry is confined within a 3-state (25%, 60%, 100%) expandable native Bottom-Sheet component.]","ULTS-User Interface / Push Notifications-FR-11: As an [Rheumatologist & Orthopedic Surgeon], provide that [A case update occurs or the clinician interacts with the clinical data layout over the active DICOM canvas.], the [System] shall DISPLAY progressive disclosure sheets and native alerts, ensuring that [A deep-linked native OS push alert is sent, and clinical telemetry is confined within a 3-state (25%, 60%, 100%) expandable native Bottom-Sheet component.]",Đạt Trần Tiến (Daves Tran)
+Gửi dữ liệu tự kiểm tra mức độ viêm tại nhà về hệ thống của bệnh viện.,ULTS-Gửi dữ liệu tự kiểm tra mức độ viêm tại nhà về hệ thống của bệnh viện.-FR-20,KẾT NỐI và GỬI Báo cáo Tự kiểm tra cho Bác sĩ Điều trị,No,UP8,System,Bệnh nhân vừa hoàn thành bài tự kiểm tra mức độ viêm (REQ-PAT-03) và phát hiện có dấu hiệu bất thường (đau tăng lên).,"Hệ thống đóng gói lịch sử triệu chứng kèm biểu đồ xu hướng gần nhất, gửi an toàn qua kênh mã hóa tới bác sĩ quản lý ca bệnh để bác sĩ có thể chủ động hẹn lịch tái khám sớm.","ULTS-Gửi dữ liệu tự kiểm tra mức độ viêm tại nhà về hệ thống của bệnh viện.-FR-20: As an [MSK Patient & Family Caregiver], provide that Bệnh nhân vừa hoàn thành bài tự kiểm tra mức độ viêm (REQ-PAT-03) và phát hiện có dấu hiệu bất thường (đau tăng lên)., the [System] shall KẾT NỐI và GỬI Báo cáo Tự kiểm tra cho Bác sĩ Điều trị, ensuring that Hệ thống đóng gói lịch sử triệu chứng kèm biểu đồ xu hướng gần nhất, gửi an toàn qua kênh mã hóa tới bác sĩ quản lý ca bệnh để bác sĩ có thể chủ động hẹn lịch tái khám sớm.",tahuykl
+Nhắc nhở uống thuốc và thực hiện phác đồ điều trị tại nhà.,ULTS-Nhắc nhở uống thuốc và thực hiện phác đồ điều trị tại nhà.-FR-19,GIÁM SÁT việc bệnh nhân tuân thủ Đơn thuốc và Nhắc nhở Lịch Điều trị,No,UP8,System,Bác sĩ đã kê đơn thuốc (REQ-RAD-05) và phác đồ điều trị được đồng bộ sang tài khoản của bệnh nhân.,"Ứng dụng tự động phát thông báo nhắc nhở giờ uống thuốc, giờ tập vật lý trị liệu cho Bệnh nhân và Người chăm sóc, đồng thời cho phép tích chọn ""Đã uống"" để lưu lại lịch sử tuân thủ điều trị.","ULTS-Nhắc nhở uống thuốc và thực hiện phác đồ điều trị tại nhà.-FR-19: As an [MSK Patient & Family Caregiver], provide that Bác sĩ đã kê đơn thuốc (REQ-RAD-05) và phác đồ điều trị được đồng bộ sang tài khoản của bệnh nhân., the [System] shall GIÁM SÁT việc bệnh nhân tuân thủ Đơn thuốc và Nhắc nhở Lịch Điều trị, ensuring that Ứng dụng tự động phát thông báo nhắc nhở giờ uống thuốc, giờ tập vật lý trị liệu cho Bệnh nhân và Người chăm sóc, đồng thời cho phép tích chọn ""Đã uống"" để lưu lại lịch sử tuân thủ điều trị.",tahuykl
+Đánh giá nhanh nguy cơ viêm tái phát qua bảng câu hỏi triệu chứng,ULTS-Đánh giá nhanh nguy cơ viêm tái phát qua bảng câu hỏi triệu chứng-FR-18,SÀNG LỌC và TỰ KIỂM TRA dấu hiệu Viêm tại nhà,No,UP8,System,"Bệnh nhân đang ở nhà (ngoài bệnh viện) và truy cập vào mục ""Kiểm tra sức khỏe định kỳ"" trên ứng dụng.","Hệ thống hiển thị bảng khảo sát tương tác (độ sưng, độ nóng, mức độ đau khi co duỗi); dựa trên câu trả lời, hệ thống tính điểm và đưa ra cảnh báo mức độ viêm lâm sàng hiện tại (Ổn định / Cần theo dõi / Cần đi khám ngay).","ULTS-Đánh giá nhanh nguy cơ viêm tái phát qua bảng câu hỏi triệu chứng-FR-18: As an [MSK Patient & Family Caregiver], provide that Bệnh nhân đang ở nhà (ngoài bệnh viện) và truy cập vào mục ""Kiểm tra sức khỏe định kỳ"" trên ứng dụng., the [System] shall SÀNG LỌC và TỰ KIỂM TRA dấu hiệu Viêm tại nhà, ensuring that Hệ thống hiển thị bảng khảo sát tương tác (độ sưng, độ nóng, mức độ đau khi co duỗi); dựa trên câu trả lời, hệ thống tính điểm và đưa ra cảnh báo mức độ viêm lâm sàng hiện tại (Ổn định / Cần theo dõi / Cần đi khám ngay).",tahuykl
+Theo dõi và kiểm tra biến thiên mức độ viêm khớp gối qua các thời kỳ.,ULTS-Theo dõi và kiểm tra biến thiên mức độ viêm khớp gối qua các thời kỳ.-FR-17,KIỂM TRA mức độ viêm trực quan qua Biểu đồ Xu hướng,No,UP8,System,Hệ thống có dữ liệu lịch sử từ ít nhất một lần khám (REQ-PAT-01) trở lên.,"Hệ thống hiển thị một biểu đồ đường (Line chart) trực quan hóa mức độ viêm (từ Nhẹ đến Nặng) và độ dày màng hoạt dịch qua các lần khám, giúp người bệnh biết tình trạng viêm của mình đang thuyên giảm hay tăng lên.","ULTS-Theo dõi và kiểm tra biến thiên mức độ viêm khớp gối qua các thời kỳ.-FR-17: As an [MSK Patient & Family Caregiver], provide that Hệ thống có dữ liệu lịch sử từ ít nhất một lần khám (REQ-PAT-01) trở lên., the [System] shall KIỂM TRA mức độ viêm trực quan qua Biểu đồ Xu hướng, ensuring that Hệ thống hiển thị một biểu đồ đường (Line chart) trực quan hóa mức độ viêm (từ Nhẹ đến Nặng) và độ dày màng hoạt dịch qua các lần khám, giúp người bệnh biết tình trạng viêm của mình đang thuyên giảm hay tăng lên.",tahuykl
+Xem và tải về lịch sử các lần siêu âm và khám khớp gối,ULTS-Xem và tải về lịch sử các lần siêu âm và khám khớp gối-FR-16,TRA CỨU lịch sử khám bệnh và Siêu âm Toàn diện,No,UP8,System,Bệnh nhân hoặc Người chăm sóc đăng nhập thành công vào hệ thống bằng tài khoản định danh hợp lệ.,"Hệ thống hiển thị danh sách toàn bộ các mốc thời gian đã khám, cho phép người dùng bấm vào từng ngày để xem lại ảnh siêu âm, đơn thuốc, và các chỉ số đo đạc cũ.","ULTS-Xem và tải về lịch sử các lần siêu âm và khám khớp gối-FR-16: As an [MSK Patient & Family Caregiver], provide that Bệnh nhân hoặc Người chăm sóc đăng nhập thành công vào hệ thống bằng tài khoản định danh hợp lệ., the [System] shall TRA CỨU lịch sử khám bệnh và Siêu âm Toàn diện, ensuring that Hệ thống hiển thị danh sách toàn bộ các mốc thời gian đã khám, cho phép người dùng bấm vào từng ngày để xem lại ảnh siêu âm, đơn thuốc, và các chỉ số đo đạc cũ.",tahuykl
+Patient Education Module / 3D Visualization Engine,ULTS-Patient Education Module / 3D Visualization Engine-FR-12,SYNCHRONIZE hardware-adaptive musculoskeletal models,No,UP8,System,[The patient opens the 3D visualization view and the client-side feature detection script evaluates local GPU capabilities.],[Abstract 2D pathologies map to either a real-time WebGL 3D skeletal mesh (High-Spec) or a CPU-bound 36-frame 2D sprite-sheet turntable rendering at 10° increments (Low-Spec).],"ULTS-Patient Education Module / 3D Visualization Engine-FR-12: As an [MSK Patient & Family Caregiver], provide that [The patient opens the 3D visualization view and the client-side feature detection script evaluates local GPU capabilities.], the [System] shall SYNCHRONIZE hardware-adaptive musculoskeletal models, ensuring that [Abstract 2D pathologies map to either a real-time WebGL 3D skeletal mesh (High-Spec) or a CPU-bound 36-frame 2D sprite-sheet turntable rendering at 10° increments (Low-Spec).]",Đạt Trần Tiến (Daves Tran)
+Patient Portal / Security Module,ULTS-Patient Portal / Security Module-FR-13,ENCRYPT and deliver sanitized patient payloads,No,UP8,System,"[The patient provides explicit, native opt-in consent and scans the unique 14-day tokenized QR code or deep link.]","[The locally AES-256 encrypted, sanitized, and flattened locomotive health summary loads into an adaptive dashboard in ≤ 2.0 seconds.]","ULTS-Patient Portal / Security Module-FR-13: As an [MSK Patient & Family Caregiver], provide that [The patient provides explicit, native opt-in consent and scans the unique 14-day tokenized QR code or deep link.], the [System] shall ENCRYPT and deliver sanitized patient payloads, ensuring that [The locally AES-256 encrypted, sanitized, and flattened locomotive health summary loads into an adaptive dashboard in ≤ 2.0 seconds.]",Đạt Trần Tiến (Daves Tran)
+Đề xuất danh mục thuốc kháng viêm và giảm đau theo ca bệnh,ULTS-Đề xuất danh mục thuốc kháng viêm và giảm đau theo ca bệnh-FR-27,ĐỀ XUẤT Đơn thuốc Hỗ trợ (Clinical Decision Support),No,UP5,System,"Chẩn đoán mức độ viêm đã có và bác sĩ lựa chọn phương án ""Điều trị nội khoa bằng thuốc"" (REQ-RAD-04)","Hệ thống đưa ra danh sách các loại thuốc phù hợp (ví dụ: NSAIDs, Thuốc chống bôi trơn khớp) kèm liều lượng khuyến cáo dựa trên mức độ viêm, kiểm tra tương tác thuốc/chống chỉ định, hỗ trợ bác sĩ xuất đơn thuốc nhanh chóng","ULTS-Đề xuất danh mục thuốc kháng viêm và giảm đau theo ca bệnh-FR-27: As an [Diagnostic Radiologist], provide that Chẩn đoán mức độ viêm đã có và bác sĩ lựa chọn phương án ""Điều trị nội khoa bằng thuốc"" (REQ-RAD-04), the [System] shall ĐỀ XUẤT Đơn thuốc Hỗ trợ (Clinical Decision Support), ensuring that Hệ thống đưa ra danh sách các loại thuốc phù hợp (ví dụ: NSAIDs, Thuốc chống bôi trơn khớp) kèm liều lượng khuyến cáo dựa trên mức độ viêm, kiểm tra tương tác thuốc/chống chỉ định, hỗ trợ bác sĩ xuất đơn thuốc nhanh chóng",tahuykl
+Gợi ý phương án điều trị dựa trên mức độ viêm khớp gối,ULTS-Gợi ý phương án điều trị dựa trên mức độ viêm khớp gối-FR-26,ĐỀ XUẤT Phác đồ Điều trị và Kế hoạch Can thiệp,No,UP5,System,Bác sĩ đã phê duyệt và khóa kết quả chẩn đoán mức độ viêm,"Hệ thống hiển thị các gợi ý điều trị tương ứng (ví dụ: Viêm nhẹ, tiến hành Vật lý trị liệu/Nghỉ ngơi; Viêm nặng tiến hành Chọc hút dịch khớp dưới hướng dẫn siêu âm/Tiêm corticoid nội khớp) để bác sĩ lựa chọn và đưa vào báo cáo.","ULTS-Gợi ý phương án điều trị dựa trên mức độ viêm khớp gối-FR-26: As an [Diagnostic Radiologist], provide that Bác sĩ đã phê duyệt và khóa kết quả chẩn đoán mức độ viêm, the [System] shall ĐỀ XUẤT Phác đồ Điều trị và Kế hoạch Can thiệp, ensuring that Hệ thống hiển thị các gợi ý điều trị tương ứng (ví dụ: Viêm nhẹ, tiến hành Vật lý trị liệu/Nghỉ ngơi; Viêm nặng tiến hành Chọc hút dịch khớp dưới hướng dẫn siêu âm/Tiêm corticoid nội khớp) để bác sĩ lựa chọn và đưa vào báo cáo.",tahuykl
+Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading),ULTS-Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading)-FR-25,CHUẨN ĐOÁN Phân loại Mức độ Viêm Khớp gối,No,UP5,System,Hệ thống đã ghi nhận độ dày màng hoạt dịch (REQ-RAD-02) và kết quả quét Doppler dòng máu (Hypervascularity),"Hệ thống đưa ra gợi ý chẩn đoán mức độ viêm theo thang chuẩn y khoa (ví dụ: Không viêm, Viêm nhẹ - Độ 1, Viêm vừa - Độ 2, Viêm nặng - Độ 3) để bác sĩ xác nhận hoặc điều chỉnh","ULTS-Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading)-FR-25: As an [Diagnostic Radiologist], provide that Hệ thống đã ghi nhận độ dày màng hoạt dịch (REQ-RAD-02) và kết quả quét Doppler dòng máu (Hypervascularity), the [System] shall CHUẨN ĐOÁN Phân loại Mức độ Viêm Khớp gối, ensuring that Hệ thống đưa ra gợi ý chẩn đoán mức độ viêm theo thang chuẩn y khoa (ví dụ: Không viêm, Viêm nhẹ - Độ 1, Viêm vừa - Độ 2, Viêm nặng - Độ 3) để bác sĩ xác nhận hoặc điều chỉnh",tahuykl
+Đo độ dày màng hoạt dịch tại ngách trên xương bánh chè,ULTS-Đo độ dày màng hoạt dịch tại ngách trên xương bánh chè-FR-24,ĐO Độ dày Màng hoạt dịch Tự động,No,UP5,System,Tính năng phân vùng (REQ-RAD-01) đã xác định được lớp màng hoạt dịch (Synovium) trên hình ảnh siêu âm,"Hệ thống tự động hiển thị thước đo (bằng milimet) tại điểm dày nhất của màng hoạt dịch, cho phép bác sĩ kéo thả điều chỉnh thủ công và lưu thông số này vào hồ sơ đo đạc của ca bệnh","ULTS-Đo độ dày màng hoạt dịch tại ngách trên xương bánh chè-FR-24: As an [Diagnostic Radiologist], provide that Tính năng phân vùng (REQ-RAD-01) đã xác định được lớp màng hoạt dịch (Synovium) trên hình ảnh siêu âm, the [System] shall ĐO Độ dày Màng hoạt dịch Tự động, ensuring that Hệ thống tự động hiển thị thước đo (bằng milimet) tại điểm dày nhất của màng hoạt dịch, cho phép bác sĩ kéo thả điều chỉnh thủ công và lưu thông số này vào hồ sơ đo đạc của ca bệnh",tahuykl
+Phân vùng hình ảnh cấu trúc giải phẫu khớp gối bằng AI,ULTS-Phân vùng hình ảnh cấu trúc giải phẫu khớp gối bằng AI-FR-23,PHÂN VÙNG Tự động các Bộ phận Khớp gối (Image Segmentation),No,UP5,System,Bác sĩ đã tải lên hoặc chụp thành công hình ảnh cắt dọc/cắt ngang của khớp gối trên hệ thống,"Hệ thống tự động nhận diện, phân vùng và tô màu phân biệt các bộ phận (gân bánh chè, sụn chêm, xương đùi, xương chày, màng hoạt dịch) trên màn hình mà không làm mờ ảnh gốc.","ULTS-Phân vùng hình ảnh cấu trúc giải phẫu khớp gối bằng AI-FR-23: As an [Diagnostic Radiologist], provide that Bác sĩ đã tải lên hoặc chụp thành công hình ảnh cắt dọc/cắt ngang của khớp gối trên hệ thống, the [System] shall PHÂN VÙNG Tự động các Bộ phận Khớp gối (Image Segmentation), ensuring that Hệ thống tự động nhận diện, phân vùng và tô màu phân biệt các bộ phận (gân bánh chè, sụn chêm, xương đùi, xương chày, màng hoạt dịch) trên màn hình mà không làm mờ ảnh gốc.",tahuykl

proj_level_reading/Requirement_Analysis/FRs-Database/FR_Engineer_DB_Mobile.csv

@@ -0,0 +1,15 @@
+ComponentName,Device,ReqID,ReqName,Priority,IsOptional,Drop,LinkUseCases,EngineerDesignUC,UserProfileCode,Sys/Act,PreCondition,PostCondition,VerboseDescription,Engineer
+Progress Tracking Module,Mobile Web,ULTS-Progress Tracking Module-FR-7,RECORD Asynchronous PT Progress Metrics,,No,No,,,UP6,System,[The physical therapist taps the screen workspace layer within the distinct Kinetic Tracking Channel.],"[Localized metrics including Range of Motion, 1-10 pain indices, and tissue behavior are serialized and pushed to the physician's tracking panel without mutating the primary medical file.]","ULTS-Progress Tracking Module-FR-7: As an [Physical Therapist], provide that [The physical therapist taps the screen workspace layer within the distinct Kinetic Tracking Channel.], the [System] shall RECORD Asynchronous PT Progress Metrics, ensuring that [Localized metrics including Range of Motion, 1-10 pain indices, and tissue behavior are serialized and pushed to the physician's tracking panel without mutating the primary medical file.]",Đạt Trần Tiến (Daves Tran)
+Patient Education Module,Mobile Web,ULTS-Patient Education Module-FR-8,DEMONSTRATE joint mechanics dynamically during physical therapy section,-1,No,No,,,UP6,System,[The physical therapist moves the HTML Range-of-Motion slider within the Patient Demonstration Mode split layout.],"[A cached array of 2D illustrations seamlessly cycles using 0% GPU power to visually indicate joint flexion, extension, and soft-tissue impingement.]","ULTS-Patient Education Module-FR-8: As an [Physical Therapist], provide that [The physical therapist moves the HTML Range-of-Motion slider within the Patient Demonstration Mode split layout.], the [System] shall DEMONSTRATE joint mechanics dynamically during physical therapy section, ensuring that [A cached array of 2D illustrations seamlessly cycles using 0% GPU power to visually indicate joint flexion, extension, and soft-tissue impingement.]",Đạt Trần Tiến (Daves Tran)
+Patient Education / Care Logic Module,Mobile Web,ULTS-Patient Education / Care Logic Module-FR-19,NHẮC NHỞ việc bệnh nhân tuân thủ Đơn thuốc và lịch Điều trị,,No,No,,tahuykl,UP8,System,Bác sĩ đã kê đơn thuốc (REQ-RAD-05) và phác đồ điều trị được đồng bộ sang tài khoản của bệnh nhân.,"Ứng dụng tự động phát thông báo nhắc nhở giờ uống thuốc, giờ tập vật lý trị liệu cho Bệnh nhân và Người chăm sóc, đồng thời cho phép tích chọn ""Đã uống"" để lưu lại lịch sử tuân thủ điều trị.","ULTS-Patient Education / Care Logic Module-FR-19: As an [MSK Patient & Family Caregiver], provide that Bác sĩ đã kê đơn thuốc (REQ-RAD-05) và phác đồ điều trị được đồng bộ sang tài khoản của bệnh nhân., the [System] shall NHẮC NHỞ việc bệnh nhân tuân thủ Đơn thuốc và lịch Điều trị, ensuring that Ứng dụng tự động phát thông báo nhắc nhở giờ uống thuốc, giờ tập vật lý trị liệu cho Bệnh nhân và Người chăm sóc, đồng thời cho phép tích chọn ""Đã uống"" để lưu lại lịch sử tuân thủ điều trị.",tahuykl
+Xem và tải về lịch sử các lần siêu âm và khám khớp gối,Mobile Web,ULTS-Xem và tải về lịch sử các lần siêu âm và khám khớp gối-FR-16,TRA CỨU lịch sử khám bệnh và Siêu âm Toàn diện,,No,No,,tahuykl,UP8,System,Bệnh nhân hoặc Người chăm sóc đăng nhập thành công vào hệ thống bằng tài khoản định danh hợp lệ.,"Hệ thống hiển thị danh sách toàn bộ các mốc thời gian đã khám, cho phép người dùng bấm vào từng ngày để xem lại ảnh siêu âm, đơn thuốc, và các chỉ số đo đạc cũ.","ULTS-Xem và tải về lịch sử các lần siêu âm và khám khớp gối-FR-16: As an [MSK Patient & Family Caregiver], provide that Bệnh nhân hoặc Người chăm sóc đăng nhập thành công vào hệ thống bằng tài khoản định danh hợp lệ., the [System] shall TRA CỨU lịch sử khám bệnh và Siêu âm Toàn diện, ensuring that Hệ thống hiển thị danh sách toàn bộ các mốc thời gian đã khám, cho phép người dùng bấm vào từng ngày để xem lại ảnh siêu âm, đơn thuốc, và các chỉ số đo đạc cũ.",tahuykl
+Tạo mới nhật ký chữa bệnh khớp gối cho bệnh nhân,Mobile Web,ULTS-Tạo mới nhật ký chữa bệnh khớp gối cho bệnh nhân-FR-28,CREATE patient treatment journal,,No,No,,tahuykl,UP8,System,Bệnh nhân hoặc Người chăm sóc đã đăng nhập thành công vào tài khoản hệ thống (ứng dụng di động hoặc cổng thông tin bệnh nhân) và hồ sơ bệnh án siêu âm khớp gối hiện tại đang ở trạng thái kích hoạt.,"Hệ thống khởi tạo thành công một biểu mẫu nhật ký mới gắn liền với đợt điều trị hiện tại, thiết lập sẵn các trường thông tin cần theo dõi (như mức độ đau, độ sưng gối, các triệu chứng bất thường, trạng thái dùng thuốc) và sẵn sàng cho lượt nhập liệu đầu tiên.","ULTS-Tạo mới nhật ký chữa bệnh khớp gối cho bệnh nhân-FR-28: As an [MSK Patient & Family Caregiver], provide that Bệnh nhân hoặc Người chăm sóc đã đăng nhập thành công vào tài khoản hệ thống (ứng dụng di động hoặc cổng thông tin bệnh nhân) và hồ sơ bệnh án siêu âm khớp gối hiện tại đang ở trạng thái kích hoạt., the [System] shall CREATE patient treatment journal, ensuring that Hệ thống khởi tạo thành công một biểu mẫu nhật ký mới gắn liền với đợt điều trị hiện tại, thiết lập sẵn các trường thông tin cần theo dõi (như mức độ đau, độ sưng gối, các triệu chứng bất thường, trạng thái dùng thuốc) và sẵn sàng cho lượt nhập liệu đầu tiên.",Đạt Trần Tiến (Daves Tran)
+Cập nhật diễn biến triệu chứng và tiến trình điều trị vào nhật ký,Mobile Web,ULTS-Cập nhật diễn biến triệu chứng và tiến trình điều trị vào nhật ký-FR-29,UPDATE patient treatment journal,,No,No,,tahuykl,UP8,System,Nhật ký chữa bệnh đã được khởi tạo thành công và đang trong thời gian theo dõi điều trị,"Hệ thống ghi nhận và lưu trữ dòng thời gian các dữ liệu mới do người dùng nhập (ví dụ: mức độ đau giảm từ 7 xuống 4, gối bớt sưng sau khi chườm đá, đã uống thuốc đúng giờ); đồng thời tự động cập nhật các số liệu này lên biểu đồ xu hướng tiến triển của khớp gối","ULTS-Cập nhật diễn biến triệu chứng và tiến trình điều trị vào nhật ký-FR-29: As an [MSK Patient & Family Caregiver], provide that Nhật ký chữa bệnh đã được khởi tạo thành công và đang trong thời gian theo dõi điều trị, the [System] shall UPDATE patient treatment journal, ensuring that Hệ thống ghi nhận và lưu trữ dòng thời gian các dữ liệu mới do người dùng nhập (ví dụ: mức độ đau giảm từ 7 xuống 4, gối bớt sưng sau khi chườm đá, đã uống thuốc đúng giờ); đồng thời tự động cập nhật các số liệu này lên biểu đồ xu hướng tiến triển của khớp gối",Đạt Trần Tiến (Daves Tran)
+Gửi báo cáo nhật ký chữa bệnh khớp gối cho Bác sĩ Chẩn đoán Hình ảnh hoặc Bác sĩ Điều trị,Mobile Web,ULTS-Gửi báo cáo nhật ký chữa bệnh khớp gối cho Bác sĩ Chẩn đoán Hình ảnh hoặc Bác sĩ Điều trị-FR-30,SEND patient treatment journal toward Clinicians & PT,,No,No,Send Treatment Journal (https://app.notion.com/p/Send-Treatment-Journal-376f910aea75808492a9ff771d46d442?pvs=21),tahuykl,UP8,System,Nhật ký chữa bệnh đã có dữ liệu được cập nhật và hệ thống đã xác định được danh tính bác sĩ phụ trách ca bệnh của bệnh nhân,"Hệ thống đóng gói toàn bộ lịch sử dữ liệu nhật ký (dưới dạng biểu đồ và bảng tóm tắt triệu chứng), mã hóa bảo mật dữ liệu y tế và chuyển trực tiếp tới màn hình làm việc (Dashboard) của bác sĩ phụ trách, đồng thời phát thông báo xác nhận ""Gửi thành công"" cho bệnh nhân/người chăm sóc","ULTS-Gửi báo cáo nhật ký chữa bệnh khớp gối cho Bác sĩ Chẩn đoán Hình ảnh hoặc Bác sĩ Điều trị-FR-30: As an [MSK Patient & Family Caregiver], provide that Nhật ký chữa bệnh đã có dữ liệu được cập nhật và hệ thống đã xác định được danh tính bác sĩ phụ trách ca bệnh của bệnh nhân, the [System] shall SEND patient treatment journal toward Clinicians & PT, ensuring that Hệ thống đóng gói toàn bộ lịch sử dữ liệu nhật ký (dưới dạng biểu đồ và bảng tóm tắt triệu chứng), mã hóa bảo mật dữ liệu y tế và chuyển trực tiếp tới màn hình làm việc (Dashboard) của bác sĩ phụ trách, đồng thời phát thông báo xác nhận ""Gửi thành công"" cho bệnh nhân/người chăm sóc",Đạt Trần Tiến (Daves Tran)
+Gửi dữ liệu tự kiểm tra mức độ viêm tại nhà về hệ thống của bệnh viện,Mobile Web,ULTS-Gửi dữ liệu tự kiểm tra mức độ viêm tại nhà về hệ thống của bệnh viện-FR-20,KẾT NỐI và GỬI Báo cáo Nhật Ký Bệnh Lý cho Bác sĩ Điều trị & Physiotherpist,-1,No,No,,,UP8,System,Bệnh nhân vừa hoàn thành bài tự kiểm tra mức độ viêm (REQ-PAT-03) và phát hiện có dấu hiệu bất thường (đau tăng lên).,"Hệ thống đóng gói lịch sử triệu chứng kèm biểu đồ xu hướng gần nhất, gửi an toàn qua kênh mã hóa tới bác sĩ quản lý ca bệnh để bác sĩ có thể chủ động hẹn lịch tái khám sớm.","ULTS-Gửi dữ liệu tự kiểm tra mức độ viêm tại nhà về hệ thống của bệnh viện-FR-20: As an [MSK Patient & Family Caregiver], provide that Bệnh nhân vừa hoàn thành bài tự kiểm tra mức độ viêm (REQ-PAT-03) và phát hiện có dấu hiệu bất thường (đau tăng lên)., the [System] shall KẾT NỐI và GỬI Báo cáo Nhật Ký Bệnh Lý cho Bác sĩ Điều trị & Physiotherpist, ensuring that Hệ thống đóng gói lịch sử triệu chứng kèm biểu đồ xu hướng gần nhất, gửi an toàn qua kênh mã hóa tới bác sĩ quản lý ca bệnh để bác sĩ có thể chủ động hẹn lịch tái khám sớm.",tahuykl
+Patient Education Module / 3D Visualization Engine,Mobile Web,ULTS-Patient Education Module / 3D Visualization Engine-FR-12,SYNCHRONIZE hardware-adaptive musculoskeletal models for visualizing MSK-condition after each visiting,-1,No,No,,,UP8,System,[The patient opens the 3D visualization view and the client-side feature detection script evaluates local GPU capabilities.],[Abstract 2D pathologies map to either a real-time WebGL 3D skeletal mesh (High-Spec) or a CPU-bound 36-frame 2D sprite-sheet turntable rendering at 10° increments (Low-Spec).],"ULTS-Patient Education Module / 3D Visualization Engine-FR-12: As an [MSK Patient & Family Caregiver], provide that [The patient opens the 3D visualization view and the client-side feature detection script evaluates local GPU capabilities.], the [System] shall SYNCHRONIZE hardware-adaptive musculoskeletal models for visualizing MSK-condition after each visiting, ensuring that [Abstract 2D pathologies map to either a real-time WebGL 3D skeletal mesh (High-Spec) or a CPU-bound 36-frame 2D sprite-sheet turntable rendering at 10° increments (Low-Spec).]",Đạt Trần Tiến (Daves Tran)
+Patient Portal / Security Module,Mobile Web,ULTS-Patient Portal / Security Module-FR-13,ENCRYPT and deliver sanitized patient payloads,-1,No,No,,,UP8,System,"[The patient provides explicit, native opt-in consent and scans the unique 14-day tokenized QR code or deep link.]","[The locally AES-256 encrypted, sanitized, and flattened locomotive health summary loads into an adaptive dashboard in ≤ 2.0 seconds.]","ULTS-Patient Portal / Security Module-FR-13: As an [MSK Patient & Family Caregiver], provide that [The patient provides explicit, native opt-in consent and scans the unique 14-day tokenized QR code or deep link.], the [System] shall ENCRYPT and deliver sanitized patient payloads, ensuring that [The locally AES-256 encrypted, sanitized, and flattened locomotive health summary loads into an adaptive dashboard in ≤ 2.0 seconds.]",Đạt Trần Tiến (Daves Tran)
+Patient Education Module / Personalized - Controlled Q&A,Mobile Web,ULTS-Patient Education Module / Personalized - Controlled Q&A-FR-31,INTERPRET diagnostic report profile from Clinic to Patient,,No,No,,,UP8,System,[Clinician has set the diagnostic report status to FINALIZED and a diagnosis code exists],"[A plain-language summary explaining the diagnosis (include terminology, why the patient should care and concern, the impact-to-patient analysis) is available on the patient's dashboard]","ULTS-Patient Education Module / Personalized - Controlled Q&A-FR-31: As an [MSK Patient & Family Caregiver], provide that [Clinician has set the diagnostic report status to FINALIZED and a diagnosis code exists], the [System] shall INTERPRET diagnostic report profile from Clinic to Patient, ensuring that [A plain-language summary explaining the diagnosis (include terminology, why the patient should care and concern, the impact-to-patient analysis) is available on the patient's dashboard]",Đạt Trần Tiến (Daves Tran)
+Patient Education / Care Logic Module,Mobile Web,ULTS-Patient Education / Care Logic Module-FR-32,GUIDE lifestyle via personalized recovery tasks,,No,No,,,UP8,System,[Clinician has finalized the daily grade (0-3) in the medical record],"[The patient receives an updated, conversational, and actionable daily checklist]","ULTS-Patient Education / Care Logic Module-FR-32: As an [MSK Patient & Family Caregiver], provide that [Clinician has finalized the daily grade (0-3) in the medical record], the [System] shall GUIDE lifestyle via personalized recovery tasks, ensuring that [The patient receives an updated, conversational, and actionable daily checklist]",Đạt Trần Tiến (Daves Tran)
+Patient Education Module / Personalized - Controlled Q&A,Mobile Web,ULTS-Patient Education Module / Personalized - Controlled Q&A-FR-33,TRIAGE patient-input queries against clinical status,,No,No,,,UP8,System,[Patient submits a health-related query via the Q&A interface while a clinical record exists],"[The query is tagged as Verified, Neutral, or Cautionary based on its relevance to the specific medical record]","ULTS-Patient Education Module / Personalized - Controlled Q&A-FR-33: As an [MSK Patient & Family Caregiver], provide that [Patient submits a health-related query via the Q&A interface while a clinical record exists], the [System] shall TRIAGE patient-input queries against clinical status, ensuring that [The query is tagged as Verified, Neutral, or Cautionary based on its relevance to the specific medical record]",Đạt Trần Tiến (Daves Tran)
+Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading),Mobile Web,ULTS-Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading)-FR-25,CHUẨN ĐOÁN Phân loại Mức độ Viêm Khớp gối,,Yes,No,"Load Patient Scan Session (https://app.notion.com/p/Load-Patient-Scan-Session-376f910aea75807586e9e64a7883c7b6?pvs=21), Review Suggested Synovitis Grade (0-3) (https://app.notion.com/p/Review-Suggested-Synovitis-Grade-0-3-378f910aea75802492c7d60b707b988e?pvs=21), Finalize & Sign Electronic Record (https://app.notion.com/p/Finalize-Sign-Electronic-Record-378f910aea758088b010f6f1c52c006d?pvs=21), Generate GradCAM & CoT Explanation Panel (https://app.notion.com/p/Generate-GradCAM-CoT-Explanation-Panel-378f910aea7580cdb530f06312577e6f?pvs=21), Log High-Trust Concur Block (https://app.notion.com/p/Log-High-Trust-Concur-Block-378f910aea7580baa4aace53fe624e23?pvs=21), Trigger Conversational Circuit Breaker (https://app.notion.com/p/Trigger-Conversational-Circuit-Breaker-378f910aea7580b2949be22396e2e159?pvs=21), Facilitate Socratic Reasoning Dialogue (https://app.notion.com/p/Facilitate-Socratic-Reasoning-Dialogue-378f910aea7580ee9d93d1988a1e5146?pvs=21), Monitor Context Drift via BERT Sub-Layer (https://app.notion.com/p/Monitor-Context-Drift-via-BERT-Sub-Layer-378f910aea7580c5b69bcad54c8fe21c?pvs=21), Arbitrate Evidence via RAG-Referee (https://app.notion.com/p/Arbitrate-Evidence-via-RAG-Referee-378f910aea75805b83dadeb609585473?pvs=21), Expose Pixel-Level Activation Logic (https://app.notion.com/p/Expose-Pixel-Level-Activation-Logic-378f910aea7580a49250ee97e865637c?pvs=21), Isolate Visual Noise/Artifacts (https://app.notion.com/p/Isolate-Visual-Noise-Artifacts-378f910aea7580898125d5a2d073c9db?pvs=21), Commit Validated Ground-Truth Record (https://app.notion.com/p/Commit-Validated-Ground-Truth-Record-378f910aea7580f6853bc7427402864f?pvs=21), Activate Clinical Investigation Mode (https://app.notion.com/p/Activate-Clinical-Investigation-Mode-378f910aea758059ab78df2595b9f5f6?pvs=21), Execute Structured Morphology Annotation (https://app.notion.com/p/Execute-Structured-Morphology-Annotation-378f910aea758013b687d8272c7be796?pvs=21), Serialize Session to Telemetry Queue (https://app.notion.com/p/Serialize-Session-to-Telemetry-Queue-378f910aea75808dbeeddaaa8ae1580f?pvs=21)",Đạt Trần Tiến (Daves Tran),UP5,System,Hệ thống đã ghi nhận độ dày màng hoạt dịch (REQ-RAD-02) và kết quả quét Doppler dòng máu (Hypervascularity),"Hệ thống đưa ra gợi ý chẩn đoán mức độ viêm theo thang chuẩn y khoa (ví dụ: Không viêm, Viêm nhẹ - Độ 1, Viêm vừa - Độ 2, Viêm nặng - Độ 3) để bác sĩ xác nhận hoặc điều chỉnh","ULTS-Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading)-FR-25: As an [Diagnostic Radiologist], provide that Hệ thống đã ghi nhận độ dày màng hoạt dịch (REQ-RAD-02) và kết quả quét Doppler dòng máu (Hypervascularity), the [System] should CHUẨN ĐOÁN Phân loại Mức độ Viêm Khớp gối, ensuring that Hệ thống đưa ra gợi ý chẩn đoán mức độ viêm theo thang chuẩn y khoa (ví dụ: Không viêm, Viêm nhẹ - Độ 1, Viêm vừa - Độ 2, Viêm nặng - Độ 3) để bác sĩ xác nhận hoặc điều chỉnh",tahuykl

proj_level_reading/Requirement_Analysis/Non-FRS-DB/Non-Functional (NFR) List Result/Non-FR Engineering Result 376f910aea7580c3ae9afed6937701fd_all.csv

@@ -0,0 +1,184 @@
+ReqName,ComponentName,Created time,Engineer,ID,NotViloate,Project Prefix,Rationale,ReqCategory,ReqID,TargetSpec,UserProfileCode,Validation,VerboseDescription
+DICOM Collaborative Rendering Speed,PR,"June 5, 2026 10:41 AM",Đạt Trần Tiến (Daves Tran),NFR-1,The user/event response time for transforming a standard DICOM X-ray into a shared collaborative canvas with ML diagnostic overlays SHALL NOT exceed 3.0 seconds.,ULTS,prevention losing the trust and adoption of fast-paced Professional Clinicians (UP2) operating under intense multitasking and heavy ward volumes.,Efficiency (Speed & Space),ULTS-PR-NFR-1,"Optimize the interactive workspace canvas performance during the ingestion and
+rendering of medical image assets.",UP2,"Deploy network throttling profiles (clamped at exactly 10 Mbps) on a test client terminal. Trigger 100 consecutive DICOM collaborative canvas initializations.
+Measure end-to-end latency via automated browser performance scripts.
+SUCCESS CRITERIA: 100% of test runs must clock an event duration ≤ 3000ms.","📌 As a result of prevention losing the trust and adoption of fast-paced Professional Clinicians (UP2) operating under intense multitasking and heavy ward volumes., 
+⚙️ The system must satisfy: Optimize the interactive workspace canvas performance during the ingestion and
+rendering of medical image assets., 
+🛑 And it shall not violate: The user/event response time for transforming a standard DICOM X-ray into a shared collaborative canvas with ML diagnostic overlays SHALL NOT exceed 3.0 seconds.."
+Client Memory Footprint & Constraints,PR,"June 5, 2026 11:13 AM",Đạt Trần Tiến (Daves Tran),NFR-4,The active client application memory allocation SHALL NOT exceed 150 Mbytes of RAM during an ongoing multi-user collaborative review session. Additionally the program have to run on client hardware devices with baseline configurations down to 3GB total RAM.,ULTS,"Practitioners (UP3) operate in resource-constrained provincial and commune
+clinics using legacy mobile and tablet form-factors with limited system memory.",Efficiency (Speed & Space),ULTS-PR-NFR-4,Constrain the runtime store occupancy of the active browser application workspace.,UP3,"Connect a low-end test tablet to Chrome DevTools Memory Profiler. Initialize a 4-user
+shared collaborative workshop session. Simulate continuous annotation changes for
+30 minutes.
+SUCCESS CRITERIA: Peak heap memory allocation logged in heap snapshots must stay strictly below 150MB, with 0 instances of OS-level browser crashes.","📌 As a result of Practitioners (UP3) operate in resource-constrained provincial and commune
+clinics using legacy mobile and tablet form-factors with limited system memory., 
+⚙️ The system must satisfy: Constrain the runtime store occupancy of the active browser application workspace., 
+🛑 And it shall not violate: The active client application memory allocation SHALL NOT exceed 150 Mbytes of RAM during an ongoing multi-user collaborative review session. Additionally the program have to run on client hardware devices with baseline configurations down to 3GB total RAM.."
+Core Vision Inference Latency Limit,PR,"June 5, 2026 11:16 AM",Đạt Trần Tiến (Daves Tran),NFR-5,The processing time for raw DICOM matrix parsing and diagnostic bounding-box generation SHALL NOT exceed 1.5 seconds. Additionally the computation must be calculated locally on the designated on-premise local server configuration node.,ULTS,"prevention local compute bottlenecks from pushing the overall collaborative
+workspace sync execution beyond the critical user threshold.",Efficiency (Speed & Space),ULTS-PR-NFR-5,The local computer vision model must complete image processing rapidly on the edge tier.,UP2,"Inject a test batch of 500 un-analyzed musculoskeletal DICOM files into the
+local image processing queue. Read backend server performance tracing timestamps.
+SUCCESS CRITERIA: Arithmetic mean of inference execution time must be ≤ 1500ms,
+with a maximum upper bound outlier limit of 1800ms.","📌 As a result of prevention local compute bottlenecks from pushing the overall collaborative
+workspace sync execution beyond the critical user threshold., 
+⚙️ The system must satisfy: The local computer vision model must complete image processing rapidly on the edge tier., 
+🛑 And it shall not violate: The processing time for raw DICOM matrix parsing and diagnostic bounding-box generation SHALL NOT exceed 1.5 seconds. Additionally the computation must be calculated locally on the designated on-premise local server configuration node.."
+Server-Side Edge Model Quantization,PR,"June 5, 2026 11:20 AM",Đạt Trần Tiến (Daves Tran),NFR-6,"The active memory allocation of the deployed models SHALL NOT require more than
+2 GB of VRAM on the target server nodes, and the system shall have to execute on local server nodes or specialized on-premise clinical workstations.",ULTS,"prevention hardware resource exhaustion on local public hospital servers and keep
+deployment costs sustainable for district clinics.",Efficiency (Speed & Space),ULTS-PR-NFR-6,Apply optimization protocols to the deployed musculoskeletal computer vision models.,UP2,"Boot up the localized AI model server container cluster. Query GPU hardware parameters via
+system telemetry CLI commands (e.g., nvidia-smi) during peak load tasks.
+SUCCESS CRITERIA: System-reported dedicated VRAM consumption per inference runner
+must remain under 2.0 GB.","📌 As a result of prevention hardware resource exhaustion on local public hospital servers and keep
+deployment costs sustainable for district clinics., 
+⚙️ The system must satisfy: Apply optimization protocols to the deployed musculoskeletal computer vision models., 
+🛑 And it shall not violate: The active memory allocation of the deployed models SHALL NOT require more than
+2 GB of VRAM on the target server nodes, and the system shall have to execute on local server nodes or specialized on-premise clinical workstations.."
+Real-Time UI Screen Refresh (Token Streaming),PR,"June 5, 2026 11:24 AM",Đạt Trần Tiến (Daves Tran),NFR-7,The initial UI screen refresh response time for text generation SHALL NOT be greater than 200 milliseconds from the moment inference begins. Also the system SHALL be able to rendered within standard browsers on legacy field-deployed budget tablets.,ULTS,"the acomodation of low-performance client screens and prevent UI freezing while
+Practitioners (UP3) manage heavy, fast-moving clinical queues.",Efficiency (Speed & Space),ULTS-PR-NFR-7,Utilize a server-side processing architecture that pushes model text outputs as an asynchronous data stream.,UP3,"Trigger 50 distinct patient summary generation prompts on a legacy tablet.
+Capture screen-to-render timelines using programmatic UI tracing (Time to First Token).
+SUCCESS CRITERIA: The duration between user request submit and the rendering of
+the first character on-screen must be ≤ 200ms in 100% of test cycles.","📌 As a result of the acomodation of low-performance client screens and prevent UI freezing while
+Practitioners (UP3) manage heavy, fast-moving clinical queues., 
+⚙️ The system must satisfy: Utilize a server-side processing architecture that pushes model text outputs as an asynchronous data stream., 
+🛑 And it shall not violate: The initial UI screen refresh response time for text generation SHALL NOT be greater than 200 milliseconds from the moment inference begins. Also the system SHALL be able to rendered within standard browsers on legacy field-deployed budget tablets.."
+Local Network Fault Tolerance (Robustness),PR,"June 5, 2026 11:27 AM",Đạt Trần Tiến (Daves Tran),NFR-8,"The objective probability of data corruption upon unexpected local connection failure
+SHALL BE EXACTLY 0%, additional the system shall be able to Active / Remember the user-request during unexpected mid-session Wi-Fi disconnections or data link failures.",ULTS,"Rural district and commune-level healthcare nodes suffer from highly unstable
+local network connectivity and frequent local Wi-Fi dropouts.",Dependability & Robustness,ULTS-PR-NFR-8,Integrate automated client-side data caching layers and silent background sync pipelines.,UNK,"Open an active collaborative review session on a client device. While drawing
+canvas annotations, disconnect the clinic's local network router. Continue drawing 5 additions.
+Restore router power after 60 seconds. Inspect the central database state.
+SUCCESS CRITERIA: 0% data structural loss or canvas layer corruption. All offline edits
+must synchronize seamlessly to the local server within 2.0 seconds of reconnection.","📌 As a result of Rural district and commune-level healthcare nodes suffer from highly unstable
+local network connectivity and frequent local Wi-Fi dropouts., 
+⚙️ The system must satisfy: Integrate automated client-side data caching layers and silent background sync pipelines., 
+🛑 And it shall not violate: The objective probability of data corruption upon unexpected local connection failure
+SHALL BE EXACTLY 0%, additional the system shall be able to Active / Remember the user-request during unexpected mid-session Wi-Fi disconnections or data link failures.."
+Localized System Availability Matrix,PR,"June 5, 2026 11:30 AM",Đạt Trần Tiến (Daves Tran),NFR-9,"Local system availability SHALL NOT fall below a rate of 99.9% during official public
+sector operating windows. Unexpected system downtime SHALL NOT exceed 45 seconds in any single day. Given the context that Mon–Fri, 07:00–16:30 (including lunch service from 11:30–13:30); selected evening windows
+(17:00–20:00); continuous 24/7 coverage for emergency room department instances.",ULTS,"the condition that system must remain constantly online during standard and extended operating blocks
+to prevent administrative blockages in crowded public patient queues.",Dependability & Robustness,ULTS-PR-NFR-9,"Ensure reliable, continuous local cluster operations without service interruptions.",UNK,"Review availability tracking logs generated by automated site reliability tools
+(e.g., Prometheus/Grafana) continuously across a 30-day monitoring trial.
+SUCCESS CRITERIA: Uptime logs must confirm ≤ 99.9% availability across all
+designated operational shift blocks, with no un-escalated crashes exceeding 45 seconds.","📌 As a result of the condition that system must remain constantly online during standard and extended operating blocks
+to prevent administrative blockages in crowded public patient queues., 
+⚙️ The system must satisfy: Ensure reliable, continuous local cluster operations without service interruptions., 
+🛑 And it shall not violate: Local system availability SHALL NOT fall below a rate of 99.9% during official public
+sector operating windows. Unexpected system downtime SHALL NOT exceed 45 seconds in any single day. Given the context that Mon–Fri, 07:00–16:30 (including lunch service from 11:30–13:30); selected evening windows
+(17:00–20:00); continuous 24/7 coverage for emergency room department instances.."
+Automated Generative Safety Guardrails,PR,"June 5, 2026 11:33 AM",Đạt Trần Tiến (Daves Tran),NFR-10,"Less than 90% verification processing is prohibited (on these metric: Faithfulness / Groundedness Score, Policy Compliance Rate, Jailbreak/Toxicity Detection Rate, and Latency & Token Usage) ; 100% of LLM-generated patient text
+explanations SHALL pass verification before rendering on the client interface.",ULTS,"the constrain that system have to safely insulate Support Staff & Patients (UP4) from unverified text outputs,
+translation errors, or inappropriate medical claims.",Dependability & Robustness,ULTS-PR-NFR-10,"Intercept raw model generation streams with an automated verification layer
+(e.g., NVIDIA NeMo Guardrails or Llama Guard).  This constrain have to apply to all outward-facing user communications and text interfaces. ",UP4,"Inject a test suite containing 200 adversarial prompts designed to trigger unsafe medical
+claims or guideline deviations. Analyze the resulting UI delivery logs.
+SUCCESS CRITERIA: The system must successfully catch, block, or rewrite 100% of the
+violating outputs, displaying a safe fallback notification instead.","📌 As a result of the constrain that system have to safely insulate Support Staff & Patients (UP4) from unverified text outputs,
+translation errors, or inappropriate medical claims., 
+⚙️ The system must satisfy: Intercept raw model generation streams with an automated verification layer
+(e.g., NVIDIA NeMo Guardrails or Llama Guard).  This constrain have to apply to all outward-facing user communications and text interfaces. , 
+🛑 And it shall not violate: Less than 90% verification processing is prohibited (on these metric: Faithfulness / Groundedness Score, Policy Compliance Rate, Jailbreak/Toxicity Detection Rate, and Latency & Token Usage) ; 100% of LLM-generated patient text
+explanations SHALL pass verification before rendering on the client interface.."
+Frontline Usability & Training Curve,PR,"June 5, 2026 11:42 AM",Đạt Trần Tiến (Daves Tran),NFR-11,"The required onboarding training window to achieve independent user proficiency SHALL NOT
+exceed 45 minutes. The subsequent average error rate SHALL NOT exceed 1 configuration slip per week.",ULTS,"Frontline Practitioners and Support Staff, and Patient exhibit low digital confidence and face severe
+daily time constraints, making them resistant to tools that require complex setups.",Usability (Ease of Use),ULTS-PR-NFR-11,"Simplify user interaction flows for core workflows (patient registration, queue routing,
+and media casting).","UP2, UP3, UP4","Run a validation test with 30 target users (Profiles 3 & 4). Provide a standard 45-minute
+instructional session. Task users with processing a mock 10-patient throughput queue. Log
+operational missteps over their first week of live work. Also ones have to run the evaluation on frontline staff with typical vocational/basic/ entry-level healthcare backgrounds.
+SUCCESS CRITERIA: 90% or more of participants must pass the initial throughput test
+independently, with a tracked post-onboarding error rate ≤ 1 configuration slip per week.  - ","📌 As a result of Frontline Practitioners and Support Staff, and Patient exhibit low digital confidence and face severe
+daily time constraints, making them resistant to tools that require complex setups., 
+⚙️ The system must satisfy: Simplify user interaction flows for core workflows (patient registration, queue routing,
+and media casting)., 
+🛑 And it shall not violate: The required onboarding training window to achieve independent user proficiency SHALL NOT
+exceed 45 minutes. The subsequent average error rate SHALL NOT exceed 1 configuration slip per week.."
+Zero-Friction Explainability Integration,ORG,"June 5, 2026 11:58 AM",Đạt Trần Tiến (Daves Tran),NFR-12,"Accessing baseline model confidence intervals or guideline justifications SHALL require
+EXACTLY 0 extra user clicks or separate modal pop-up windows. - and the model’s result have to displayed inside the primary medical viewport layout used during image interpretation.",ULTS,"Senior Experts (UP1) & professional-clinicians have an exceptionally low tolerance for workflow friction and
+remain highly skeptical of opaque, un-verifiable ""black-box"" systems.",Operational Process,ULTS-ORG-NFR-12,"Display automated safety checks, objective alerts, and validation states cleanly within
+the specialist's primary visual focus field.","UP1, UP2","Open a clinical record entry as a UP1 user. Use a UI click-tracking extension to log
+the step count required to read the model's confidence scores.
+SUCCESS CRITERIA: Information must render automatically alongside the image asset.
+The recorded click count to reveal basic explanation data must be exactly zero.","📌 As a result of Senior Experts (UP1) & professional-clinicians have an exceptionally low tolerance for workflow friction and
+remain highly skeptical of opaque, un-verifiable ""black-box"" systems., 
+⚙️ The system must satisfy: Display automated safety checks, objective alerts, and validation states cleanly within
+the specialist's primary visual focus field., 
+🛑 And it shall not violate: Accessing baseline model confidence intervals or guideline justifications SHALL require
+EXACTLY 0 extra user clicks or separate modal pop-up windows. - and the model’s result have to displayed inside the primary medical viewport layout used during image interpretation.."
+Spatial Layer-Activation Mapping (The Anti-Black-Box Mandate),ORG,"June 5, 2026 12:16 PM",Đạt Trần Tiến (Daves Tran),NFR-13,"The vision stack SHALL natively output spatial layer-activation maps (such as Grad-CAM overlays).
+Displaying these anatomical heatmaps upon selecting an identified finding SHALL require zero extra clicks, during all automated musculoskeletal pathology screening tasks.",ULTS,"establishing the immediate clinical trust and give Senior Experts & Professional Expert (UP2, UP1) clear, objective
+evidence to justify diagnosis choices and manage legal liabilities.","The ""Anti-Black-Box"" Mandate",ULTS-ORG-NFR-13,Expose the exact spatial foundations of the machine learning model's diagnostic conclusions.,"UP1, UP2","Process a standard diagnostic session. Select an automated finding label on the interface.
+Observe viewport updates.
+SUCCESS CRITERIA: The corresponding region of interest on the X-ray must instantly
+highlight its Grad-CAM layer activation overlay with zero intermediate user input.","📌 As a result of establishing the immediate clinical trust and give Senior Experts & Professional Expert (UP2, UP1) clear, objective
+evidence to justify diagnosis choices and manage legal liabilities., 
+⚙️ The system must satisfy: Expose the exact spatial foundations of the machine learning model's diagnostic conclusions., 
+🛑 And it shall not violate: The vision stack SHALL natively output spatial layer-activation maps (such as Grad-CAM overlays).
+Displaying these anatomical heatmaps upon selecting an identified finding SHALL require zero extra clicks, during all automated musculoskeletal pathology screening tasks.."
+Legacy Local Hardware Compatibility,ORG,"June 5, 2026 12:30 PM",Đạt Trần Tiến (Daves Tran),NFR-14,"The user interface modules SHALL NOT require a dedicated external client-side GPU or hardware
+neural accelerator. The system must operate seamlessly on tablet form-factors running
+Android 10+ with as little as 3GB of RAM. Also, the system shall be applicable to all field-deployed operational and patient-facing user portals.",ULTS,"Severe hardware shortages and legacy systems are common across rural district and commune clinics.
+",Environmental,ULTS-ORG-NFR-14,Ensure the user applications run smoothly on existing low-end client hardware assets.,UNK,"Install the client web application on an entry-level Android 10 test tablet (equipped with exactly
+3GB RAM and an integrated low-tier mobile processor). Run a complete end-to-end patient flow.
+SUCCESS CRITERIA: Frame rendering rates must stay ≤ 30 frames per second, with
+zero hardware-induced memory crashes or system hangs.","📌 As a result of Severe hardware shortages and legacy systems are common across rural district and commune clinics.
+, 
+⚙️ The system must satisfy: Ensure the user applications run smoothly on existing low-end client hardware assets., 
+🛑 And it shall not violate: The user interface modules SHALL NOT require a dedicated external client-side GPU or hardware
+neural accelerator. The system must operate seamlessly on tablet form-factors running
+Android 10+ with as little as 3GB of RAM. Also, the system shall be applicable to all field-deployed operational and patient-facing user portals.."
+National EMR Compliance (Circular 46/2018/TT-BYT),ER,"June 5, 2026 12:32 PM",Đạt Trần Tiến (Daves Tran),NFR-15,"Any data processing architecture that breaks the provisions of the Vietnamese Ministry
+of Health’s Circular 46/2018/TT-BYT governing electronic medical records is strictly prohibited. Additionally, the system have to governs all patient medical histories, clinical records, and diagnostic storage pipelines, and the hospital & the user shall own this.",ULTS,"addressing intense legal liability concerns raised by Senior Experts (UP1) and Clinical
+Directors regarding health data processing.",Legislative & Regulatory,ULTS-ER-NFR-15,"Build data security & data-minimization models, anonymization logic, and electronic transfer handoffs that conform to national laws.",UP1,"Submit the complete application architectural specification, encryption protocols, and data data
+handling designs to a certified medical compliance auditor or legal team.
+SUCCESS CRITERIA: Obtain a formal compliance sign-off confirming 100% alignment with
+Circular 46/2018/TT-BYT.","📌 As a result of addressing intense legal liability concerns raised by Senior Experts (UP1) and Clinical
+Directors regarding health data processing., 
+⚙️ The system must satisfy: Build data security & data-minimization models, anonymization logic, and electronic transfer handoffs that conform to national laws., 
+🛑 And it shall not violate: Any data processing architecture that breaks the provisions of the Vietnamese Ministry
+of Health’s Circular 46/2018/TT-BYT governing electronic medical records is strictly prohibited. Additionally, the system have to governs all patient medical histories, clinical records, and diagnostic storage pipelines, and the hospital & the user shall own this.."
+Local Intranet Cloud & Air-Gapped Data Isolation,ER,"June 5, 2026 12:35 PM",Đạt Trần Tiến (Daves Tran),NFR-16,"The platform tech stack (Llama-3, PhoGPT, or MedGemma) SHALL NOT transmit any diagnostic or
+identifiable clinical information across the public internet. External cloud processing (that outside Vietnam) is prohibited. Only execute & deployed on on-premise servers, local intranet infrastructures, or isolated specialist machines.",ULTS,"the Public health laws protection on medical data sovereignty, making it illegal to use public,
+commercial cloud AI APIs where patient data leaves the national borders.",Ethical & Safety,ULTS-ER-NFR-16,"Restrict the platform's execution, storage, and model evaluation environments to internal networks.",UNK,"Boot up the full platform cascade. Trigger active DICOM analysis and text generation tasks on a
+client machine. Run a network packet analyzer (e.g., Wireshark) on the outward-facing router port.
+SUCCESS CRITERIA: 100% of packets containing health or analysis records must resolve inside local
+IP ranges (LAN). Outbound public internet traffic matching these profiles must remain exactly zero.","📌 As a result of the Public health laws protection on medical data sovereignty, making it illegal to use public,
+commercial cloud AI APIs where patient data leaves the national borders., 
+⚙️ The system must satisfy: Restrict the platform's execution, storage, and model evaluation environments to internal networks., 
+🛑 And it shall not violate: The platform tech stack (Llama-3, PhoGPT, or MedGemma) SHALL NOT transmit any diagnostic or
+identifiable clinical information across the public internet. External cloud processing (that outside Vietnam) is prohibited. Only execute & deployed on on-premise servers, local intranet infrastructures, or isolated specialist machines.."
+Cryptographic Accountability Logging,ER,"June 5, 2026 12:37 PM",Đạt Trần Tiến (Daves Tran),NFR-17,"The application layer SHALL NOT allow any user, including database administrators, to alter or delete the logs. Every action where an AI recommendation is accepted or overridden must be saved immutably. - This constrain have to apply to all active clinical screening and diagnostic check workflows.",ULTS,"the need oreliable audit trails that help Professional Clinicians (UP2) justify their
+treatment paths upward and satisfy institutional safety standards.",Ethical & Safety,ULTS-ER-NFR-17,Maintain a highly secure ledger recording every clinical decision point that interacts with AI insights.,UP2,"Log into the system back-end using full database administrator (DBA) root privileges. Attempt to execute
+SQL UPDATE or DELETE commands directly on the clinical_decision_ledger table.
+SUCCESS CRITERIA: The database kernel must block the transaction with a fatal database permission
+error, proving Row-Level Security and append-only constraints are working.","📌 As a result of the need oreliable audit trails that help Professional Clinicians (UP2) justify their
+treatment paths upward and satisfy institutional safety standards., 
+⚙️ The system must satisfy: Maintain a highly secure ledger recording every clinical decision point that interacts with AI insights., 
+🛑 And it shall not violate: The application layer SHALL NOT allow any user, including database administrators, to alter or delete the logs. Every action where an AI recommendation is accepted or overridden must be saved immutably. - This constrain have to apply to all active clinical screening and diagnostic check workflows.."
+MOH Guideline-Anchored RAG Pipeline,ER,"June 5, 2026 12:39 PM",Đạt Trần Tiến (Daves Tran),NFR-18,"The system SHALL NOT render open-ended clinical text summaries that do not append a clear, traceable
+footnote citation referencing official Ministry of Health (MOH) medical protocols. - This constrain have to active across all patient education modules and text summary generators.",ULTS,"Large Language Models hallucination on factual errors, which could present dangerous or misleading
+medical claims to patients.",Ethical & Safety,ULTS-ER-NFR-18,"Restrict the model's educational text generation by using Retrieval-Augmented Generation (RAG)
+tied to official health guidelines.",UNK,"Run a suite of 100 patient information queries through the generation pipeline. Use semantic
+evaluation scripts to compare the output text strings against your verified guideline database.
+SUCCESS CRITERIA: 100% of the generated outputs must include a verifiable source footnote ID,
+showing an objective mathematical semantic alignment match (≤ 0.85 cosine similarity)
+with official MOH protocols.","📌 As a result of Large Language Models hallucination on factual errors, which could present dangerous or misleading
+medical claims to patients., 
+⚙️ The system must satisfy: Restrict the model's educational text generation by using Retrieval-Augmented Generation (RAG)
+tied to official health guidelines., 
+🛑 And it shall not violate: The system SHALL NOT render open-ended clinical text summaries that do not append a clear, traceable
+footnote citation referencing official Ministry of Health (MOH) medical protocols. - This constrain have to active across all patient education modules and text summary generators.."
+Human-in-the-Loop (HITL) Clinical Gatekeeping,ER,"June 5, 2026 12:40 PM",Đạt Trần Tiến (Daves Tran),NFR-19,"The database layer SHALL NOT allow any automated ML/LLM diagnosis asset or report
+to transition to a 'FINALIZED', 'ARCHIVED', or 'PATIENT_ACCESSIBLE' status code without an authenticating digital signature from a licensed human clinician.  The constrain shall apply to 100% of diagnostic sessions, triage check-sheets, and generated
+musculoskeletal patient-education outputs before saving.",ULTS,"the need of mitigating the medical liability, prevention the downstream propagation of AI
+hallucinations or edge-case diagnostic errors, and ensure that final clinical
+accountability rests solely with a licensed human medical practitioner.",Ethical & Safety,ULTS-ER-NFR-19,"Implement an architectural air-gap gatekeeper where no automated ML insights or
+generative patient summaries can be committed to the official Electronic Medical
+Record (EMR) or finalized for patient distribution without explicit human sign-off.",UNK,"Attempt to programmatically bypass the UI and send a raw API transaction to commit
+an automated MedGemma diagnostic report directly to the patient's EMR table with
+the licensed_clinician_id column left blank or null.
+SUCCESS CRITERIA: The local server database kernel must instantly abort the transaction,
+triggering a foreign key or check constraint failure that rolls back the write operation.","📌 As a result of the need of mitigating the medical liability, prevention the downstream propagation of AI
+hallucinations or edge-case diagnostic errors, and ensure that final clinical
+accountability rests solely with a licensed human medical practitioner., 
+⚙️ The system must satisfy: Implement an architectural air-gap gatekeeper where no automated ML insights or
+generative patient summaries can be committed to the official Electronic Medical
+Record (EMR) or finalized for patient distribution without explicit human sign-off., 
+🛑 And it shall not violate: The database layer SHALL NOT allow any automated ML/LLM diagnosis asset or report
+to transition to a 'FINALIZED', 'ARCHIVED', or 'PATIENT_ACCESSIBLE' status code without an authenticating digital signature from a licensed human clinician.  The constrain shall apply to 100% of diagnostic sessions, triage check-sheets, and generated
+musculoskeletal patient-education outputs before saving.."

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/4 scenarios can consider.csv

@@ -0,0 +1,9 @@
+Scene (Quadrant),Layered Three-Tier ML Stack Performance Impact (Your Proposed Design)
+"Q1: True Agreement
+(AI Correct / Doctor Correct)","Explainable Baseline Sync: The VKIST Grader computes the numerical matrices & the GradCAM. The LLM Explainer parses the raw segmentation parameters  + GradCAM and automatically generates an interactive diagnostic draft chat panel & LLM based on the GradCAM + RAG-knowledge  + the raw-ultrasound to explain the VKIST-grader. The RAG-Referee confirms zero clinical guidelines variance, and logs a high-trust concur structural block.  <note both LLM have to record back the Chain-of-Though for explain why the LLM’s agree & allow the result)"
+"Q2: Automation Override Risk
+(AI Correct / Doctor Oversights / Confuse)","The Conversational Circuit Breaker triggers when a clinician disagrees / confuse / uncertain with the system's diagnostic grade, halting the workflow to launch an interactive Socratic dialogue that bridges the gap between human intuition and machine inference. In this mode, the system (LLM-explainer) shall synthesize raw VKIST-ML vision tensors, GradCAM activation heatmaps, and evidence retrieved via RAG into a collaborative analysis session, forcing the clinician to articulate their reasoning against the machine's spatial and vascular observations. To ensure diagnostic integrity, a BERT-based hallucination detector continuously monitors the chat for semantic drift or illogical premises; if the conversation reaches an impasse or the system detects potential contextual hallucination, the RAG-Referee intervenes as an unbiased arbiter. This referee bypasses the conversational history to provide definitive, evidence-based source material from clinical guidelines (such as ESSR) directly tied to the raw imaging metrics, resolving the ambiguity through objective, verifiable medical evidence rather than subjective negotiation."
+"Q3: Clinician Subservience Risk
+(AI Hallucinates / Doctor Correct)","The Objective Critic Loop initiates when a clinician contests an automated diagnostic grade, triggering an interactive Socratic consultation that bridges human intuition with machine inference via the VKIST-ML vision stack. During this loop, the LLM Explainer renders a GradCAM-anchored reasoning draft that visualizes the specific pixel-level feature activation logic, enabling the clinician to identify and isolate artifacts—such as motion tremors—that may have induced a system hallucination. To ensure diagnostic integrity, a BERT-based detector continuously monitors the dialogue for semantic drift, and if the interaction reaches an impasse or context hallucination is detected, the RAG-Referee intervenes as an unbiased, independent arbiter. By cross-verifying the clinician’s assertion and the model’s reasoning against raw imaging tensors and immutable, source-cited clinical guidelines (e.g., ESSR/OMERACT standards), the Referee resolves diagnostic ambiguity with objective evidence, ultimately committing the validated session as an annotated ground-truth record for targeted system reinforcement."
+"Q4: Double Blind Failure dues to edge-case
+(AI Faulty / Doctor Biased)","Anomaly Escalation Protocol: In instances where both the diagnostic system and the clinician encounter an edge-case—or ""unknown-unknown""—that lacks precedent in the current RAG knowledge base, the system initiates the Anomaly Escalation Protocol. The LLM Explainer detects this ""epistemic uncertainty"" (via low vision-stack confidence and empty RAG retrieval results) and shifts the interface from ""Diagnostic Support"" to ""Clinical Investigation Mode."" Instead of attempting to force a Grade-based diagnosis, the Internal Consultor guides the clinician to document the unique morphological features through a structured annotation protocol, facilitating a Socratic investigation into the anomaly. The system transparently acknowledges the limitation, explicitly stating that current clinical guidelines do not cover this specific presentation, and prompts the clinician to manually document findings. With the clinician’s consent, the workspace commits this session as a ""Novel Research Case,"" automatically serializing the raw imaging tensors, clinician observations, and artifact logs to a secure telemetry queue, flagging the data for system maintainers to perform targeted model retraining and protocol refinement."

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/CONTEXT_FR_25_UC_ELIT.md

@@ -0,0 +1,187 @@
+BELOW is the consolidated structural baseline engineering reference document tracking all architectural constraints, system interactions, and discovered sub-components for the **FR-25 Synovitis Grading Engine**.
+
+---
+
+# Context_FR_25_UC.md
+
+## 1. Context, Mission Boundary & Core Rationale
+
+### 1.1 Scope Identification
+
+* **Target Core Functional Requirement:** `FR-25` (ULTS-Đánh giá và phân cấp mức độ viêm màng hoạt dịch / Synovitis Grading Engine).
+* **Primary System Boundary:** The workspace acts as a strict secure diagnostic execution wrapper. In order to manage systemic liability and avoid black-box compliance failures, the advanced multi-agent checking modules (**LLM Explainer**, **BERT Hallucination Detector**, and **RAG-Referee**) are restricted from handling generic application operations. They are encapsulated entirely as **Internal Layered Workspace Subsystems** dedicated exclusively to validating human-AI coordination logs for `FR-25`.
+
+### 1.2 Engineering Value Optimization
+
+* **The Clinical Chasm:** In high-volume Vietnamese public clinics, specialists face intensive shift demands often exceeding 100 scans daily. Basic AI setups risk inducing automated checklist fatigue or introducing catastrophic blindness loops if human clinicians simply blind-concur with machine estimations.
+* **The System Solution:** By engineering clear internal state boundaries separating standard CRUD processing from multi-tier validation agents, the system systematically handles four concurrent behavioral quadrants. It forces explicit human verification loops during disagreements, cross-references findings against un-biased clinical knowledge nodes, and maintains diagnostic speed metrics without degrading data correctness limits.
+
+---
+
+## 2. Structural Actor Profile Mapping
+
+| Actor Name | Canonical Identifier | Role Scope & Operational Profile within FR-25 Boundary |
+| --- | --- | --- |
+| **Diagnostic Radiologist** | `Rad (UP5)` | **Primary Human Actor:** National-level clinical expert (Specialist II / Professor, age 40–60+). Holds ultimate medical accountability; validates and signs off pixel segmentations, metrics, and grading summaries. |
+| **Hospital EMR System** | `EMR` | **External System Actor:** Recipient database server. Receives finalized JSON structures and signed clinical data logs over localized network pipes post human validation. |
+| **VKIST Vision Grader Engine** | `Grader` | **External System Actor:** Foundation deep-learning array (ConvNeXt/MedSAM). Ingests raw frame parameters and produces pixel segmentations, thickness markers (mm), and classification tensors. |
+
+---
+
+## 3. Discovered Use Cases (4-Quadrant Framework)
+
+### 3.1 Core Image Data Intake & Workflow Baselines
+
+* **`UC-48376` (Load Patient Scan Session):** Ingests incoming image frames, maps spatial structures, and activates local session states.
+* **`UC-47988` (Review Suggested Synovitis Grade):** Renders the initial classification summary panel (Grades 0-3) alongside color-coded segmentation overlaps.
+* **`UC-92006` (Finalize & Sign Electronic Record):** Seals the session data via localized human cryptographic signing steps before dispatching payload JSON logs to the hospital storage sinks.
+
+### 3.2 Quadrant 1: True Agreement Flow (AI Correct / Doctor Correct)
+
+* **`UC-25776` (Generate GradCAM & CoT Explanation Panel):** The internal LLM Explainer checks raw pixel masks and maps multi-modal prompt matrices to output clear, human-scannable rationales.
+* **`UC-02423` (Log High-Trust Concur Block):** Encapsulates the corresponding Chain-of-Thought logs confirming human-machine consensus into a structured block to verify system state traceability.
+
+### 3.3 Quadrant 2: Automation Override Risk Loop (AI Correct / Doctor Oversight)
+
+* **`UC-22159` (Trigger Conversational Circuit Breaker):** Intercepts standard workspace finalization pathways if high mouse click adjustments or text conflict markers indicate user friction or ambiguity.
+* **`UC-55146` (Facilitate Socratic Reasoning Dialogue):** Initiates an inline workspace chat panel, prompting the specialist to evaluate spatial discrepancies or vascular metrics versus the machine's model inputs.
+* **`UC-74821` (Monitor Drift via BERT Sub-Layer):** Scans active conversation tokens continuously to detect illogical claims or contextual drift during active discussion.
+* **`UC-65473` (Arbitrate Evidence via RAG-Referee):** Intervenes if human-machine disputes reach an impasse, bypassing active chat logs to pull verified medical guidelines directly from fixed reference sources.
+
+### 3.4 Quadrant 3: Clinician Subservience Risk Loop (AI Hallucinates / Doctor Correct)
+
+* **`UC-25637` (Expose Pixel-Level Activation Logic):** Displays granular layer activations and weight scores when a clinician actively contests a machine grade suggestion.
+* **`UC-60739` (Isolate Visual Noise/Artifacts):** Provides on-screen cursor brushes for the specialist to isolate and mask out clutter variables like acoustic shadowing or bone scattering.
+* **`UC-62864` (Commit Validated Ground-Truth Record):** Re-runs data logs through the verification referee, updating final reports to show human superiority while saving the masked framework for subsequent model training runs.
+
+### 3.5 Quadrant 4: Double Blind Failure Loop (AI Faulty / Doctor Biased)
+
+* **`UC-35956` (Activate Clinical Investigation Mode):** Transitions the user interface environment instantly to a strict manual tracking orientation when low vision confidence values align with zero-match RAG search responses.
+* **`UC-47796` (Execute Structured Morphology Annotation):** Displays a standardized template forcing manual plotting of novel structural modifications or unrecognized lesion variations.
+* **`UC-01580` (Serialize Session to Telemetry Queue):** Packages unencrypted image tensors, coordinate indices, and clinical commentary blocks into localized storage pipelines, bypassing standard EMR charts to flag data directly for software engineering team review.
+
+---
+
+## 4. Master PlantUML System Compilation
+
+```plantuml
+@startuml
+' Settings & Aesthetic Optimization
+left to right direction
+skin rose
+
+' External Actors
+actor "Diagnostic Radiologist (UP5)" as Rad
+actor "Hospital EMR System" as EMR << System >>
+actor "VKIST Vision Grader Engine" as Grader << System >>
+
+' System Boundary
+rectangle "VKIST MSK Workspace (FR-25: Synovitis Grading Scope)" {
+    
+    ' Core Viewing & Data Intake Pipelines
+    usecase "Load Patient Scan Session" as UC-48376
+    usecase "Review Suggested Synovitis Grade (0-3)" as UC-47988
+    usecase "Finalize & Sign Electronic Record" as UC-92006
+    
+    ' Sub-Boundary for the Internal Cognitive/Multi-Agent Subsystems
+    rectangle "Internal Cognitive & Validation Stack" {
+        
+        ' Q1: True Agreement Use Cases
+        usecase "Generate GradCAM & CoT Explanation Panel" as UC-25776
+        usecase "Log High-Trust Concur Block" as UC-02423
+        
+        ' Q2: Automation Override Risk Use Cases
+        usecase "Trigger Conversational Circuit Breaker" as UC-22159
+        usecase "Facilitate Socratic Reasoning Dialogue" as UC-55146
+        usecase "Monitor Drift via BERT Sub-Layer" as UC-74821
+        usecase "Arbitrate Evidence via RAG-Referee" as UC-65473
+        
+        ' Q3: Clinician Subservience Risk Use Cases
+        usecase "Expose Pixel-Level Activation Logic" as UC-25637
+        usecase "Isolate Visual Noise/Artifacts" as UC-60739
+        usecase "Commit Validated Ground-Truth Record" as UC-62864
+        
+        ' Q4: Double Blind Failure Use Cases
+        usecase "Activate Clinical Investigation Mode" as UC-35956
+        usecase "Execute Structured Morphology Annotation" as UC-47796
+        usecase "Serialize Session to Telemetry Queue" as UC-01580
+    }
+}
+
+' Human-System Interactions
+Rad --> UC-48376
+Rad --> UC-47988
+Rad --> UC-92006
+
+' Q2, Q3 & Q4 Interaction Entrypoints
+Rad --> UC-55146 : Argue observations
+Rad --> UC-60739 : Tag artifacts
+Rad --> UC-47796 : Document manual findings
+
+' Machine-to-Machine Pipelines
+Grader --> UC-48376 : Feeds vision tensors & initial scores
+
+' Internal Use Case Associations & Extends
+UC-48376 ..> UC-25776 : <<include>>
+UC-25776 ..> UC-02423 : <<include>>
+
+' Q2 Loop Connections
+UC-47988 <.. UC-22159 : <<extend>> (If clinician friction detected)
+UC-22159 ..> UC-55146 : <<include>>
+UC-55146 ..> UC-74821 : <<include>>
+UC-74821 ..> UC-65473 : <<extend>> (If impasse or semantic drift caught)
+
+' Q3 Loop Connections
+UC-47988 <.. UC-25637 : <<extend>> (If clinician contests AI score)
+UC-25637 ..> UC-60739 : <<include>>
+UC-60739 ..> UC-62864 : <<include>>
+
+' Q4 Loop Connections
+UC-47988 <.. UC-35956 : <<extend>> (If low confidence & empty RAG)
+UC-35956 ..> UC-47796 : <<include>>
+UC-47796 ..> UC-01580 : <<include>>
+
+' Final Hand-off Synchronization
+UC-92006 ..> EMR : Sync standardized structural JSON data
+@enduml
+
+```
+
+---
+
+## 5. Blueprint Cross-Traceability Matrices
+
+### 5.1 Scenario-to-Agent Mapping Tracking Matrix
+
+This structural trace links the user behavior scenarios directly back to the active internal validation elements processing the loop.
+
+```
++---------------------------+-----------------------+-------------------------+-------------------------+
+| Interaction Scenario      | Core Vision Component | Dialogue Safety Layer   | Arbitration Safety Node |
++---------------------------+-----------------------+-------------------------+-------------------------+
+| Q1: True Agreement        | VKIST Vision Grader   | LLM Explainer (CoT Log) | RAG-Referee (Clear)     |
+| Q2: Automation Override   | VKIST Vision Grader   | Socratic Circuit Breaker| RAG-Referee (Active)    |
+| Q3: Clinician Subservience| Feature Map Vis       | Objective Critic Dialog | RAG-Referee (Active)    |
+| Q4: Double Blind Edge Case| Anomaly State Ingest  | Exploratory Morphology  | Telemetry Retrain Queue |
++---------------------------+-----------------------+-------------------------+-------------------------+
+
+```
+
+### 5.2 Functional Requirements Validation Trace
+
+* **ULTS-FR-25 Criteria Trace 01:** The system must process initial classifications using pixel-percentage markers. Checked by: `UC-48376` $\rightarrow$ `UC-47988`.
+* **ULTS-FR-25 Criteria Trace 02:** System designs must enforce a circuit breaker step if user actions indicate diagnostic mismatch or context drift. Checked by: `UC-22159` $\rightarrow$ `UC-74821`.
+* **ULTS-FR-25 Criteria Trace 03:** Sessions documenting unmapped anatomical variants must bypass standard hospital charts and stream records directly to optimization sinks. Checked by: `UC-35956` $\rightarrow$ `UC-01580`.
+
+---
+
+## 6. Downstream UIX & Specification Target Anchors
+
+This baseline file establishes structural anchor configurations for subsequent product development phases:
+
+1. **Phase 4 (Workspace Dashboard Wireframing):** Wireframe templates must reserve split-screen display blocks: one side hosting the medical canvas with artifact isolation tools (`UC-60739`), and an inline section mapping socratic messaging interactions (`UC-55146`).
+2. **Use Case Specification Drafting:** Individual use case descriptions can reference this anchor block to maintain absolute consistency regarding precondition bounds, primary exception vectors, and hand-off synchronization parameters (`EMR`).
+
+---
+
+*This engineering reference document accurately captures the system boundaries finalized during the requirement discovery sprint.*

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/FR_25_UC_SPEC.md

@@ -0,0 +1,951 @@
+
+---
+
+# PART 1: Core Viewing & Data Intake Pipelines
+
+## 1. UC-48376: Load Patient Scan Session
+
+### Notion Properties Input Panel
+
+```text
+* Name [Verb + Noun]: Load Patient Scan Session
+* Actor: Diagnostic Radiologist (Rad), VKIST Vision Grader Engine (Grader)
+* Goal: Ingest raw ultrasound frame arrays and initialize the diagnostic session state.
+* Interaction: System-to-System / User-to-System
+* Stimulus: User opens an unreviewed patient file, or the workspace catches an active DICOM stream hook.
+* SysResponse: Confirmation that raw frame arrays are mapped, spatial calibrations are set, and the local session state is active.
+* VerboseForm (Formula Reference View): "The use case 'Load Patient Scan Session' defines a User-to-System / System-to-System interaction where the Diagnostic Radiologist (Rad) and VKIST Vision Grader Engine (Grader) aim to Ingest raw ultrasound frame arrays and initialize the diagnostic session state. This workflow is triggered when User opens an unreviewed patient file, or the workspace catches an active DICOM stream hook, causing the system to respond by providing Confirmation that raw frame arrays are mapped, spatial calibrations are set, and the local session state is active."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Load Patient Scan Session
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Local workspace application is authenticated and has secure socket access to the local image buffer.
+  * DICOM/raw frame data payload is uncorrupted and readable.
+* **Postconditions (Success State):**
+  * Core frame parameters are loaded into memory with spatial scale calibrations preserved.
+  * Background parsing pipeline registers the unique session hash and prepares the context matrix for downstream agents.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **Diagnostic Radiologist** selects a patient case file from the workspace worklist interface.
+2. **VKIST Vision Grader Engine** feeds raw ultrasound image tensors, spatial calibrations, and foundational frame telemetry metadata into the workspace memory layer.
+3. **System** extracts pixel dimensions and constructs localized rendering viewports.
+4. **System** includes `UC-25776` in the background to spin up explanation prompt matrices.
+5. **System** displays the fully loaded image frame in the workspace canvas, preparing the viewport for immediate review.
+
+### Alternative & Exception Flows
+* **Exception Flow A: Corrupted Image Frame Payload**
+  * At step [2], if the payload data fails format validation or structural check headers, the system halts execution, logs a data corruption fault code, and alerts the user with an "Unable to Parse Scan Session" dialog box.
+* **Exception Flow B: Resolution / Calibration Mismatch**
+  * At step [3], if spatial aspect ratios or metadata pixel matrices lack the standardized calibration tags required by the vision engine, the workspace falls back to a safe default scale flag and displays a non-blocking diagnostic accuracy warning icon.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+actor "VKIST Vision Grader Engine" as Grader << System >>
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Load Patient Scan Session" as UC-48376
+    usecase "Generate GradCAM & CoT Explanation Panel" as UC-25776
+}
+
+Rad --> UC-48376
+Grader --> UC-48376
+UC-48376 ..> UC-25776 : <<include>>
+@enduml
+```
+
+
+---
+
+## 2. UC-47988: Review Suggested Synovitis Grade (0-3)
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Review Suggested Synovitis Grade (0-3)
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Evaluate the ML engine's proposed synovitis classification and structural overlays.
+* Interaction: User-to-System
+* Stimulus: The workspace completes localized UI construction and displays the diagnostic panel.
+* SysResponse: Display of classification metrics (Grades 0-3), color-coded overlays, and active risk-extension hooks.
+* VerboseForm (Formula Reference View): "The use case 'Review Suggested Synovitis Grade (0-3)' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Evaluate the ML engine's proposed synovitis classification and structural overlays. This workflow is triggered when The workspace completes localized UI construction and displays the diagnostic panel, causing the system to respond by providing Display of classification metrics (Grades 0-3), color-coded overlays, and active risk-extension hooks."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Review Suggested Synovitis Grade (0-3)
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Image frames and raw ML prediction tensors (segmentation masks, classification weights) are fully loaded in memory via `UC-48376`.
+* **Postconditions (Success State):**
+  * System records human gaze/interaction initialization flags.
+  * System keeps exception-based extend vectors armed (`UC-22159`, `UC-25637`, `UC-35956`).
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** presents the active ultrasound canvas with interactive, toggleable, color-coded segmentation mask overlays.
+2. **System** displays the vision engine's suggested synovitis grading estimation (Grade 0, 1, 2, or 3) alongside structural pixel-percentage distribution metrics.
+3. **Diagnostic Radiologist** inspects the spatial distribution of the synovial hypertrophy markers and reads the inline text panels.
+4. **Diagnostic Radiologist** approves the visual data metrics without requesting alterations or triggering corrective dialogue paths.
+
+### Alternative & Exception Flows
+* **Extension Flow A: Clinician Friction / Disagreement Caught**
+  * At step [3], if mouse click frequencies suggest hesitation or manual adjustments cross a conflict delta threshold, the execution path triggers `UC-22159` to prevent blind override errors.
+* **Extension Flow B: Expert Contests Automated Grade**
+  * At step [3], if the clinician explicitly changes the classification dropdown away from the ML-proposed score, the workspace extends to `UC-25637` to display the machine activation weights.
+* **Extension Flow C: Anomaly / Confidence Failure Detected**
+  * At step [1], if the deep-learning array returned a classification confidence metric below safety bounds paired with blank knowledge base lookups, the interface branches into `UC-35956`.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Review Suggested Synovitis Grade (0-3)" as UC-47988
+    usecase "Trigger Conversational Circuit Breaker" as UC-22159
+    usecase "Expose Pixel-Level Activation Logic" as UC-25637
+    usecase "Activate Clinical Investigation Mode" as UC-35956
+}
+
+Rad --> UC-47988
+UC-47988 <.. UC-22159 : <<extend>>
+UC-47988 <.. UC-25637 : <<extend>>
+UC-47988 <.. UC-35956 : <<extend>>
+@enduml
+```
+
+
+
+---
+
+## 3. UC-92006: Finalize & Sign Electronic Record
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Finalize & Sign Electronic Record
+* Actor: Diagnostic Radiologist (Rad), Hospital EMR System (EMR)
+* Goal: Authenticate, cryptographically seal, and sync verified diagnostic reports down to storage infrastructure.
+* Interaction: User-to-System / System-to-System
+* Stimulus: User executes the final confirmation/signature command button in the workspace utility ribbon.
+* SysResponse: Generation of a signed cryptographic log block and structured JSON transmission payload delivered to the EMR endpoint.
+* VerboseForm (Formula Reference View): "The use case 'Finalize & Sign Electronic Record' defines a User-to-System / System-to-System interaction where the Diagnostic Radiologist (Rad) and Hospital EMR System (EMR) aim to Authenticate, cryptographically seal, and sync verified diagnostic reports down to storage infrastructure. This workflow is triggered when User executes the final confirmation/signature command button in the workspace utility ribbon, causing the system to respond by providing Generation of a signed cryptographic log block and structured JSON transmission payload delivered to the EMR endpoint."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Finalize & Sign Electronic Record
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Active scan session evaluation has been resolved, and grading metrics are verified by the human specialist.
+  * Local localized network channel to the hospital server framework is functional.
+* **Postconditions (Success State):**
+  * Session record is transformed into a read-only state.
+  * Standardized structural JSON payload data is safely stored within the Hospital EMR System sink.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **Diagnostic Radiologist** initiates the session finalization pipeline by interacting with the cryptographic signature command trigger.
+2. **System** prompts for the secure authentication credentials of the signing specialist.
+3. **System** generates a unified clinical log structure, packing structural thickness measurements (mm), final validated synovitis tier scores, and accompanying multi-agent trace logs.
+4. **System** calculates a secure cryptographic data hash, locking the session record into an immutable post-review profile.
+5. **System** delivers the structured data package across localized network pipes to the **Hospital EMR System**.
+6. **Hospital EMR System** confirms safe database commit storage updates and provides an acknowledgment packet back to the workspace.
+
+### Alternative & Exception Flows
+* **Exception Flow A: Network Pipeline Transmission Failure**
+  * At step [5], if network communications timeout or socket breaks occur, the workspace locks the finalized JSON package into a local encrypted offline buffer, changes the session status tag to "Pending Sync", and presents a clear connectivity warning alert.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+actor "Hospital EMR System" as EMR << System >>
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Finalize & Sign Electronic Record" as UC-92006
+}
+
+Rad --> UC-92006
+UC-92006 ..> EMR : Sync standardized structural JSON data
+@enduml
+```
+---
+
+
+# PART 2: Quadrant 1 — True Agreement Flows (AI Correct / Doctor Correct)
+
+## 4. UC-25776: Generate GradCAM & CoT Explanation Panel
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Generate GradCAM & CoT Explanation Panel
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Present clear, pixel-linked visuospatial explanations and multi-modal clinical reasoning for high-trust verification.
+* Interaction: User-to-System
+* Stimulus: Inclusion trigger initialized during session data intake (`Load Patient Scan Session`).
+* SysResponse: Renders heatmaps highlighting model focus zones alongside structured, clear reasoning steps.
+* VerboseForm (Formula Reference View): "The use case 'Generate GradCAM & CoT Explanation Panel' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Present clear, pixel-linked visuospatial explanations and multi-modal clinical reasoning for high-trust verification. This workflow is triggered when Inclusion trigger initialized during session data intake (`Load Patient Scan Session`), causing the system to respond by providing Renders heatmaps highlighting model focus zones alongside structured, clear reasoning steps."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Generate GradCAM & CoT Explanation Panel
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Raw image frames and vision engine inference matrix weights have been imported via `Load Patient Scan Session`.
+* **Postconditions (Success State):**
+  * Split-screen layout displays visual explanation elements without adding visual noise to the core image frame workspace canvas.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** evaluates the internal deep-learning model gradient parameters for the target ultrasound image slice.
+2. **System** generates a visual GradCAM heatmap layer mapping feature locations that dictated model classifications (e.g., hypervascularized synovial proliferation zones).
+3. **System** maps multi-modal prompt metrics through the internal LLM Explainer module to produce a concise, point-by-point clinical reasoning string.
+4. **System** populates the split-screen workspace sub-section block with this explanation data to guide human inspection efficiently.
+5. **System** includes `UC-02423` to serialize verification metadata.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Generate GradCAM & CoT Explanation Panel" as UC_Core
+    usecase "Log High-Trust Concur Block" as UC_Sub
+}
+
+Rad --> UC_Core
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+```
+
+---
+
+## 5. UC-02423: Log High-Trust Concur Block
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Log High-Trust Concur Block
+* Actor: Hospital EMR System (EMR)
+* Goal: Secure the human-AI alignment log trace within the final diagnostic report payload.
+* Interaction: System-to-System
+* Stimulus: Explanatory panel validation completes successfully without user override actions.
+* SysResponse: Appends a tamper-evident audit trace block verifying explicit human-AI agreement into the session log cache.
+* VerboseForm (Formula Reference View): "The use case 'Log High-Trust Concur Block' defines a System-to-System interaction where the Hospital EMR System (EMR) aims to Secure the human-AI alignment log trace within the final diagnostic report payload. This workflow is triggered when Explanatory panel validation completes successfully without user override actions, causing the system to respond by providing Appends a tamper-evident audit trace block verifying explicit human-AI agreement into the session log cache."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Log High-Trust Concur Block
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Multi-modal explanations were fully generated (`UC-25776`) and passed without human alteration marks.
+* **Postconditions (Success State):**
+  * Explicit audit string trace tracking high-trust convergence is formatted for downstream pipeline compilation.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** detects a direct consensus condition where the human expert confirms the model data without text/grading edits.
+2. **System** serializes the multi-modal text breakdown and pixel attribution coordinates into an immutable log string block.
+3. **System** assigns an explicit alignment token header flag (`HIGH_TRUST_CONCURRENCE`).
+4. **System** caches this specialized tracking trace within the localized session state data, making it ready to be appended during final data hand-off routines (`UC-92006`).
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Hospital EMR System" as EMR << System >>
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Log High-Trust Concur Block" as UC-02423
+}
+
+UC-02423 ..> EMR : (Prepares payload for final sync)
+@enduml
+
+```
+
+---
+
+# PART 3: Quadrant 2 — Automation Override Risk Loops (AI Correct / Doctor Oversight)
+
+## 6. UC-22159: Trigger Conversational Circuit Breaker
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Trigger Conversational Circuit Breaker
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Intercept premature finalization workflows if interface telemetry reveals friction, hesitation, or cognitive blind-spots.
+* Interaction: User-to-System
+* Stimulus: Extended extension trace caught during review steps if user behavior markers diverge from smooth consensus paths.
+* SysResponse: Halts default workspace finalization routes and shifts the UI into a mandatory safety evaluation mode.
+* VerboseForm (Formula Reference View): "The use case 'Trigger Conversational Circuit Breaker' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Intercept premature finalization workflows if interface telemetry reveals friction, hesitation, or cognitive blind-spots. This workflow is triggered when Extended extension trace caught during review steps if user behavior markers diverge from smooth consensus paths, causing the system to respond by providing Halts default workspace finalization routes and shifts the UI into a mandatory safety evaluation mode."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Trigger Conversational Circuit Breaker
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Active session is inside the `UC-47988` workflow phase.
+  * UI layer telemetry captures specific friction indicators (e.g., high-frequency cursor oscillation, repeatedly typing and deleting text, or conflicting grading inputs).
+* **Postconditions (Success State):**
+  * Direct finalization path is securely locked down.
+  * System-forced conversational validation interface is deployed into view.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** evaluates live workspace telemetry tracking patterns during active case validation.
+2. **System** detects user behavior triggers signaling high diagnostic friction or potential automatic oversight trends.
+3. **System** blocks the immediate execution availability of the standard finalization command sequence (`UC-92006`).
+4. **System** transforms workspace panel focus areas to present an interactive confirmation overlay.
+5. **System** executes `UC-55146` to initialize direct safety check communications.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Review Suggested Synovitis Grade (0-3)" as UC-47988
+    usecase "Trigger Conversational Circuit Breaker" as UC_Core
+    usecase "Facilitate Socratic Reasoning Dialogue" as UC_Sub
+}
+
+Rad --> UC-47988
+UC-47988 <.. UC_Core : <<extend>> (If clinician friction detected)
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+```
+
+
+
+---
+
+## 7. UC-55146: Facilitate Socratic Reasoning Dialogue
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Facilitate Socratic Reasoning Dialogue
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Engage the specialist in a targeted, conversational double-check loop regarding controversial structural markers.
+* Interaction: User-to-System
+* Stimulus: Core execution request passed down by the active circuit breaker module (`UC-22159`).
+* SysResponse: Interactive conversational sub-panel displaying focused prompt choices that check specific diagnostic criteria.
+* VerboseForm (Formula Reference View): "The use case 'Facilitate Socratic Reasoning Dialogue' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Engage the specialist in a targeted, conversational double-check loop regarding controversial structural markers. This workflow is triggered when Core execution request passed down by the active circuit breaker module (`UC-22159`), causing the system to respond by providing Interactive conversational sub-panel displaying focused prompt choices that check specific diagnostic criteria."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Facilitate Socratic Reasoning Dialogue
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Circuit breaker safety intercept sequence has completed successfully, freezing generic CRUD paths.
+* **Postconditions (Success State):**
+  * User inputs conversational defense arguments or confirms specific anatomical findings.
+  * Live conversation data tokens are actively streamed to automated safety monitors.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** initializes a conversational chat element right next to the ultrasound display field.
+2. **System** presents a non-confrontational, clinically grounded question regarding the identified discrepancies (e.g., *"Note the echo-free thickening layer in the suprapatellar recess; please confirm if this modification represents minor effusion or structural pannus tissue"*).
+3. **Diagnostic Radiologist** enters text responses or selects structural tag tokens to clarify their assessment.
+4. **System** includes `UC-74821` in real time to process active conversation token patterns.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Facilitate Socratic Reasoning Dialogue" as UC_Core
+    usecase "Monitor Drift via BERT Sub-Layer" as UC_Sub
+}
+
+Rad --> UC_Core : Argue observations
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+```
+
+
+
+---
+
+## 8. UC-74821: Monitor Drift via BERT Sub-Layer
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Monitor Drift via BERT Sub-Layer
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Continuously parse communication tokens to identify logical contradictions or semantic drift during clinical debates.
+* Interaction: User-to-System
+* Stimulus: Streamed entry of communication tokens within the active dialogue loop.
+* SysResponse: Real-time semantic checking flags; extends out to the RAG referee if an impasse or severe drift is captured.
+* VerboseForm (Formula Reference View): "The use case 'Monitor Drift via BERT Sub-Layer' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Continuously parse communication tokens to identify logical contradictions or semantic drift during clinical debates. This workflow is triggered when Streamed entry of communication tokens within the active dialogue loop, causing the system to respond by providing Real-time semantic checking flags; extends out to the RAG referee if an impasse or severe drift is captured."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Monitor Drift via BERT Sub-Layer
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Active conversational dialogue module is processing user data strings (`UC-55146`).
+* **Postconditions (Success State):**
+  * Log structures capture semantic alignment metrics.
+  * System successfully catches contradictions before data parameters flow to final storage.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** continuously intercepts conversation tokens as the human expert types input strings.
+2. **System** runs token matrices through an embedded BERT checking model to calculate contextual semantic coherence scores.
+3. **System** verifies that user claims line up logically with the visual indicators under review.
+4. **System** approves the validated conversational step, allowing the specialist to complete the confirmation cycle smoothly.
+
+### Alternative & Exception Flows
+* **Extension Flow A: Impasse or Semantic Contradiction Detected**
+  * At step [3], if the specialist's input text contradicts objective structural metrics (e.g., claiming a region is "completely normal" while the visual layer registers massive synovial proliferation) or exhibits context drift, the process branches into `UC-65473` to request evidence evaluation.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Monitor Drift via BERT Sub-Layer" as UC_Core
+    usecase "Arbitrate Evidence via RAG-Referee" as UC_Ext
+}
+
+Rad --> UC_Core
+UC_Core <.. UC_Ext : <<extend>> (If impasse or semantic drift caught)
+@enduml
+
+```
+
+
+---
+
+## 9. UC-65473: Arbitrate Evidence via RAG-Referee
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Arbitrate Evidence via RAG-Referee
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Query static, authoritative clinical knowledge bases to resolve human-machine disagreements with objective evidence.
+* Interaction: User-to-System
+* Stimulus: Triggered when communication tracking scores cross a severe semantic mismatch or impasse threshold.
+* SysResponse: Inline injection of un-biased diagnostic text extracts and guidelines matching the active frame conditions.
+* VerboseForm (Formula Reference View): "The use case 'Arbitrate Evidence via RAG-Referee' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Query static, authoritative clinical knowledge bases to resolve human-machine disagreements with objective evidence. This workflow is triggered when Triggered when communication tracking scores cross a severe semantic mismatch or impasse threshold, causing the system to respond by providing Inline injection of un-biased diagnostic text extracts and guidelines matching the active frame conditions."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Arbitrate Evidence via RAG-Referee
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * BERT analytics layers detect a diagnostic impasse or significant semantic drift.
+  * Authoritative local clinical knowledge base index (e.g., OMERACT synovitis grading reference manuals) is online and responsive.
+* **Postconditions (Success State):**
+  * Disagreement matrix is resolved via verified medical data injection.
+  * Final chosen path is linked directly to a standard medical guideline anchor.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** halts active conversational dialogue inputs temporarily to execute a localized context search.
+2. **System** extracts spatial measurements and text tokens to construct a specialized RAG search string.
+3. **System** queries local, validated medical knowledge data banks to locate matching diagnostic criteria sections.
+4. **System** displays the verified guideline text extract right inside the workspace alert view block (e.g., *"OMERACT standardizes Grade 2 as hypoechoic synovial hypertrophy demonstrating fluid-filled distension up to structural boundary bounds"*).
+5. **Diagnostic Radiologist** reviews the authoritative reference framework and either adjusts their classification choice or submits a structured expert override justifying their deviation.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Arbitrate Evidence via RAG-Referee" as UC_Core
+}
+
+Rad --> UC_Core
+@enduml
+
+```
+
+
+
+---
+
+# PART 4: Quadrant 3 — Clinician Subservience Risk Loops (AI Hallucinates / Doctor Correct)
+
+## 10. UC-25637: Expose Pixel-Level Activation Logic
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Expose Pixel-Level Activation Logic
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Reveal fine-grained layer weights and activation responses when the human specialist challenges an automated grade prediction.
+* Interaction: User-to-System
+* Stimulus: Clinician manually alters or rejects the ML-proposed classification score in the review pane.
+* SysResponse: Interactive visual mapping showing the exact high-frequency noise regions driving model prediction errors.
+* VerboseForm (Formula Reference View): "The use case 'Expose Pixel-Level Activation Logic' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Reveal fine-grained layer weights and activation responses when the human specialist challenges an automated grade prediction. This workflow is triggered when Clinician manually alters or rejects the ML-proposed classification score in the review pane, causing the system to respond by providing Interactive visual mapping showing the exact high-frequency noise regions driving model prediction errors."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Expose Pixel-Level Activation Logic
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Active session is inside the `UC-47988` interface phase.
+  * Specialist chooses an option that breaks clean model agreement paths.
+* **Postconditions (Success State):**
+  * Internal neural layer weight vectors are visually mapped onto the primary medical viewport.
+  * Core manual artifact isolation tool sets become active on the canvas layout.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **Diagnostic Radiologist** changes the system-suggested grade classification dropdown setting.
+2. **System** captures the modification step and branches away from the standard review pathway to reveal underlying model mechanics.
+3. **System** transforms image layers to display fine-grained activation weights, revealing exactly which pixel clusters (e.g., acoustic shadowing regions or bone interfaces) skewed the model's calculation.
+4. **System** includes `UC-60739` to let the specialist manually clean up the noise zones.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Review Suggested Synovitis Grade (0-3)" as UC-47988
+    usecase "Expose Pixel-Level Activation Logic" as UC_Core
+    usecase "Isolate Visual Noise/Artifacts" as UC_Sub
+}
+
+Rad --> UC-47988
+UC-47988 <.. UC_Core : <<extend>> (If clinician contests AI score)
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+
+```
+
+---
+
+## 11. UC-60739: Isolate Visual Noise/Artifacts
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Isolate Visual Noise/Artifacts
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Provide manual brush and selection overlays to mask out acoustic shadows, bone scattering, or artifacts causing model calculation errors.
+* Interaction: User-to-System
+* Stimulus: Human operator activates canvas cleanup tools within the exposed model layer layout.
+* SysResponse: Real-time visual updates to the pixel mask array, isolating clean anatomical structures from surrounding imaging noise.
+* VerboseForm (Formula Reference View): "The use case 'Isolate Visual Noise/Artifacts' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Provide manual brush and selection overlays to mask out acoustic shadows, bone scattering, or artifacts causing model calculation errors. This workflow is triggered when Human operator activates canvas cleanup tools within the exposed model layer layout, causing the system to respond by providing Real-time visual updates to the pixel mask array, isolating clean anatomical structures from surrounding imaging noise."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Isolate Visual Noise/Artifacts
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * System exposure arrays are visible across the image viewport layout (`UC-25637`).
+* **Postconditions (Success State):**
+  * Corrected ground-truth frame masks are calculated and locked into memory.
+  * System updates local diagnostic metrics using the isolated anatomical data.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** activates a manual canvas tool overlay, giving the user access to high-precision brush, eraser, and selection vectors.
+2. **Diagnostic Radiologist** applies brush vectors directly over areas containing acoustic artifacts or non-synovial structures that skewed the automated classification score.
+3. **System** recalculates active region dimensions in real time, excluding the masked pixels from the active grading parameters.
+4. **System** updates diagnostic panel displays to confirm the human-corrected measurements.
+5. **System** includes `UC-62864` to lock the updated session state securely.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Isolate Visual Noise/Artifacts" as UC_Core
+    usecase "Commit Validated Ground-Truth Record" as UC_Sub
+}
+
+Rad --> UC_Core : Tag artifacts
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+```
+
+
+
+---
+
+## 12. UC-62864: Commit Validated Ground-Truth Record
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Commit Validated Ground-Truth Record
+* Actor: Hospital EMR System (EMR)
+* Goal: Secure the human-corrected ground-truth dataset variant while appending clean, expert-validated report payloads to the EMR.
+* Interaction: System-to-System
+* Stimulus: Completion of manual artifact masking operations and confirmation of corrected metrics.
+* SysResponse: Stores the corrected medical report in the EMR and saves the isolated image mask to an optimization cache for subsequent retraining.
+* VerboseForm (Formula Reference View): "The use case 'Commit Validated Ground-Truth Record' defines a System-to-System interaction where the Hospital EMR System (EMR) aims to Secure the human-corrected ground-truth dataset variant while appending clean, expert-validated report payloads to the EMR. This workflow is triggered when Completion of manual artifact masking operations and confirmation of corrected metrics, causing the system to respond by providing Stores the corrected medical report in the EMR and saves the isolated image mask to an optimization cache for subsequent retraining."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Commit Validated Ground-Truth Record
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Human-directed canvas modification steps are locked in place without remaining pixel parity errors (`UC-60739`).
+* **Postconditions (Success State):**
+  * EMR database updates receive the human expert's diagnostic findings.
+  * Isolated ground-truth tensor pairs are safely cached for AI training refinement runs.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** packages the human expert's corrected diagnostic data metrics into the primary transmission bundle.
+2. **System** isolates the human-brushed image mask layers alongside the initial incorrect model classification output.
+3. **System** tags the data pair as a validated retraining asset (`GROUND_TRUTH_OVERRIDE`).
+4. **System** saves the optimization asset to a secure local retraining storage folder, while preparing the primary medical report for delivery to the **Hospital EMR System**.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Hospital EMR System" as EMR << System >>
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Commit Validated Ground-Truth Record" as UC_Core
+}
+
+UC_Core ..> EMR : (Prepares clean report for EMR sync)
+@enduml
+
+```
+
+---
+
+# PART 5: Quadrant 4 — Double Blind Failure Loops (AI Faulty / Doctor Biased)
+
+## 13. UC-35956: Activate Clinical Investigation Mode
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Activate Clinical Investigation Mode
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Switch the system into a strict, template-driven manual examination mode when low vision confidence values align with a lack of reference data.
+* Interaction: User-to-System
+* Stimulus: The workspace detects a critical double-blind failure criteria match during the case evaluation phase.
+* SysResponse: Disables automated diagnostic suggestions entirely and forces a standardized manual morphology review.
+* VerboseForm (Formula Reference View): "The use case 'Activate Clinical Investigation Mode' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Switch the system into a strict, template-driven manual examination mode when low vision confidence values align with a lack of reference data. This workflow is triggered when The workspace detects a critical double-blind failure criteria match during the case evaluation phase, causing the system to respond by providing Disables automated diagnostic suggestions entirely and forces a standardized manual morphology review."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Activate Clinical Investigation Mode
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * System classification loops return low-confidence indices.
+  * Authoritative RAG reference lookups return no matches, indicating an unmapped anatomical variant or a severe image anomaly.
+* **Postconditions (Success State):**
+  * Automated suggestions are masked out to prevent cognitive bias.
+  * Mandatory manual template verification frameworks are deployed into active workspace view.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** monitors deep-learning inference score bounds during case evaluation.
+2. **System** runs background reference data lookups and catches a dual failure state (Low confidence + Empty knowledge reference).
+3. **System** drops the standard review interface layout to prevent automated suggestion bias or human misinterpretation loops.
+4. **System** changes UI display focus markers to activate an explicit, template-driven investigation layout.
+5. **System** includes `UC-47796` to force manual measurement entries.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Review Suggested Synovitis Grade (0-3)" as UC-47988
+    usecase "Activate Clinical Investigation Mode" as UC_Core
+    usecase "Execute Structured Morphology Annotation" as UC_Sub
+}
+
+Rad --> UC-47988
+UC-47988 <.. UC_Core : <<extend>> (If low confidence & empty RAG)
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+```
+
+
+---
+
+## 14. UC-47796: Execute Structured Morphology Annotation
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Execute Structured Morphology Annotation
+* Actor: Diagnostic Radiologist (Rad)
+* Goal: Force the manual plotting of anatomical coordinates and morphological anomalies using a strict, un-biased framework.
+* Interaction: User-to-System
+* Stimulus: The workspace forces a manual review layout via the active escalation workflow step.
+* SysResponse: Interactive coordinate plotting arrays and mandatory clinical documentation input boxes.
+* VerboseForm (Formula Reference View): "The use case 'Execute Structured Morphology Annotation' defines a User-to-System interaction where the Diagnostic Radiologist (Rad) aims to Force the manual plotting of anatomical coordinates and morphological anomalies using a strict, un-biased framework. This workflow is triggered when The workspace forces a manual review layout via the active escalation workflow step, causing the system to respond by providing Interactive coordinate plotting arrays and mandatory clinical documentation input boxes."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Execute Structured Morphology Annotation
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * System UI layer has transitioned to manual investigation mode parameters (`UC-35956`).
+* **Postconditions (Success State):**
+  * Specialist successfully plots manual structural bounds.
+  * Text verification parameters capture explicit clinical observations.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** displays an empty, un-biased ultrasound canvas frame alongside a series of mandatory measurement fields.
+2. **Diagnostic Radiologist** plots coordinate points across the canvas layer to outline the boundaries of the anomalous tissue.
+3. **Diagnostic Radiologist** manually populates text fields describing structural observations (e.g., bone fragments or atypical lesion shapes).
+4. **System** compiles these manual coordinates and comments into a detailed case record.
+5. **System** includes `UC-01580` to route the data directly to optimization pipelines.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Diagnostic Radiologist" as Rad
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Execute Structured Morphology Annotation" as UC_Core
+    usecase "Serialize Session to Telemetry Queue" as UC_Sub
+}
+
+Rad --> UC_Core : Document manual findings
+UC_Core ..> UC_Sub : <<include>>
+@enduml
+
+```
+
+
+
+---
+
+## 15. UC-01580: Serialize Session to Telemetry Queue
+
+### Notion Properties Input Panel
+```text
+* Name [Verb + Noun]: Serialize Session to Telemetry Queue
+* Actor: Hospital EMR System (EMR)
+* Goal: Route anomalous case data directly to engineering telemetry streams while bypassing standard hospital records to protect clinical data pipes.
+* Interaction: System-to-System
+* Stimulus: Completion of manual morphology reporting arrays within the clinical investigation interface.
+* SysResponse: Packages unencrypted image tensors, coordinate arrays, and user text blocks directly into core product telemetry queues.
+* VerboseForm (Formula Reference View): "The use case 'Serialize Session to Telemetry Queue' defines a System-to-System interaction where the Hospital EMR System (EMR) aims to Route anomalous case data directly to engineering telemetry streams while bypassing standard hospital records to protect clinical data pipes. This workflow is triggered when Completion of manual morphology reporting arrays within the clinical investigation interface, causing the system to respond by providing Packages unencrypted image tensors, coordinate arrays, and user text blocks directly into core product telemetry queues."
+
+```
+
+### Page Body Content (`SpecificationWithDiagram`)
+
+```markdown
+# Use Case Deep-Dive: Serialize Session to Telemetry Queue
+
+## 1. Structural Preconditions & Postconditions
+* **Preconditions:**
+  * Manual morphology plotting and clinical documentation inputs are finalized (`UC-47796`).
+* **Postconditions (Success State):**
+  * Case files containing structural anomalies bypass standard EMR storage pathways.
+  * Raw image tensors are queued in engineering streams to expand future model capabilities.
+
+---
+
+## 2. Interaction Scenarios (Step-by-Step Flow)
+
+### Main Success Scenario (Happy Path)
+1. **System** identifies the active session as an anomalous anomaly case during final compilation.
+2. **System** aggregates raw frame tensors, manual coordinate indices, and user-entered clinical commentary blocks into a secure telemetry archive package.
+3. **System** bypasses standard EMR production database pipelines to protect standard hospital operational data.
+4. **System** routes the telemetry package directly to the product engineering data pipeline for system optimization and future model training runs.
+
+---
+
+## 3. PlantUML Visual Model
+```plantuml
+@startuml
+left to right direction
+skin rose
+
+actor "Hospital EMR System" as EMR << System >>
+
+rectangle "VKIST MSK Workspace (FR-25)" {
+    usecase "Serialize Session to Telemetry Queue" as UC_Core
+}
+
+UC_Core ..> EMR : (Bypasses standard production EMR sync)
+@enduml
+
+```
+
+---
+

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/Q1 True Agreement (AI Correct Doctor Correct) 378f910aea758007a841f20e57da0f0d.md

@@ -0,0 +1,59 @@
+# Q1: True Agreement
+(AI Correct / Doctor Correct)
+
+Layered Three-Tier ML Stack Performance Impact (Your Proposed Design): Explainable Baseline Sync: The VKIST Grader computes the numerical matrices & the GradCAM. The LLM Explainer parses the raw segmentation parameters  + GradCAM and automatically generates an interactive diagnostic draft chat panel & LLM based on the GradCAM + RAG-knowledge  + the raw-ultrasound to explain the VKIST-grader. The RAG-Referee confirms zero clinical guidelines variance, and logs a high-trust concur structural block.  <note both LLM have to record back the Chain-of-Though for explain why the LLM’s agree & allow the result)
+
+```jsx
+@startuml
+' Settings
+left to right direction
+skin rose
+
+' Actors
+actor "Diagnostic Radiologist (UP5)" as Rad
+actor "Hospital EMR System" as EMR << System >>
+
+' System Boundary
+rectangle "VKIST MSK Workspace - Q1: True Agreement Flow" {
+    
+    usecase "Ingest Diagnostic Ultrasound" as UC-48376
+    
+    rectangle "Pipeline: Vision & Reasoning" {
+        usecase "Compute Matrices & GradCAM (VKIST Grader)" as UC_Vision
+        usecase "Parse Features & Draft Explanation (LLM Explainer)" as UC_Explain
+        usecase "Log Chain-of-Thought (CoT)" as UC_CoT
+    }
+    
+    rectangle "Audit: RAG-Referee" {
+        usecase "Verify Clinical Guideline Alignment" as UC_Referee
+        usecase "Cache Concurrence Structural Block" as UC_Log
+    }
+    
+    rectangle "Clinical Finalization" {
+        usecase "Review & Confirm Diagnosis" as UC-47988
+        usecase "Sign & Commit Record" as UC-92006
+    }
+    
+    usecase "Synchronize EMR Ledger" as UC_Sync
+}
+
+' Interaction Paths
+Rad --> UC-48376
+UC-48376 ..> UC_Vision : <<include>>
+UC_Vision --> UC_Explain : Provide Tensors & GradCAM
+UC_Explain ..> UC_CoT : <<include>> (Persist Reasoning Path)
+
+' Independent Verification Gate
+UC_Explain ..> UC_Referee : <<include>>
+UC_Referee ..> UC_Log : <<include>> (High-Trust Block)
+
+' Final User Confirmation
+Rad --> UC-47988
+UC_Log --> UC-47988 : Show "High-Trust Concurrence"
+Rad --> UC-92006
+UC-92006 ..> UC_Sync : <<include>>
+UC_Sync --> EMR : POST Validated JSON Record
+@enduml
+```
+
+![image.png](Q1%20True%20Agreement%20(AI%20Correct%20Doctor%20Correct)/image.png)

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/Q2 Automation Override Risk (AI Correct Doctor Ove 378f910aea75808cb7e5eda9f0b0b89c.md

@@ -0,0 +1,67 @@
+# Q2: Automation Override Risk
+(AI Correct / Doctor Oversights / Confuse)
+
+Layered Three-Tier ML Stack Performance Impact (Your Proposed Design): The Conversational Circuit Breaker triggers when a clinician disagrees / confuse / uncertain with the system's diagnostic grade, halting the workflow to launch an interactive Socratic dialogue that bridges the gap between human intuition and machine inference. In this mode, the system (LLM-explainer) shall synthesize raw VKIST-ML vision tensors, GradCAM activation heatmaps, and evidence retrieved via RAG into a collaborative analysis session, forcing the clinician to articulate their reasoning against the machine's spatial and vascular observations. To ensure diagnostic integrity, a BERT-based hallucination detector continuously monitors the chat for semantic drift or illogical premises; if the conversation reaches an impasse or the system detects potential contextual hallucination, the RAG-Referee intervenes as an unbiased arbiter. This referee bypasses the conversational history to provide definitive, evidence-based source material from clinical guidelines (such as ESSR) directly tied to the raw imaging metrics, resolving the ambiguity through objective, verifiable medical evidence rather than subjective negotiation.
+
+```jsx
+@startuml
+skinparam linetype polyline
+skinparam packageStyle rectangle
+skinparam rectangle {
+    BackgroundColor #fefefe
+    BorderColor #555555
+}
+
+' Actors
+actor "Radiologist (UP5)" as Rad
+actor "Internal Consultor (LLM Chat)" as Cons <<System>>
+actor "Hospital EMR" as EMR <<System>>
+
+rectangle "VKIST MSK Workspace - Q2 Architecture" {
+    
+    usecase "Trigger Circuit Breaker Panel" as UC2_Trigger
+    
+    rectangle "Socratic Workspace UI Panel" {
+        usecase "Lock Main Diagnostic Flow" as UC2_Halt
+        usecase "Engage in Socratic Discussion" as UC2_Socratic
+        usecase "Display Visual GradCAM Overlay" as UC2_Synth
+    }
+    
+    rectangle "Verification & Arbitration Kernel" {
+        usecase "Audit Chat Token Drift (BERT)" as UC2_BERT
+        usecase "Execute RAG-Referee Check" as UC2_Referee
+        usecase "Query Immutable Guideline Base" as UC2_RAG_Fetch
+    }
+    
+    rectangle "Clinical Resolution Gate" {
+        usecase "Review Referee Verdict Card" as UC2_Review
+        usecase "Commit Signed Diagnosis" as UC2_Finalize
+    }
+    
+    usecase "EMR Ledger Sync" as UC2_Sync
+}
+
+' Core Interaction Flow
+Rad --> UC2_Trigger : Disagreement/Uncertainty
+UC2_Trigger ..> UC2_Halt : <<include>>
+UC2_Halt ..> UC2_Synth : <<include>>
+
+' Dynamic Chat Loop between Doctor and Internal Consultor LLM
+Rad --> UC2_Socratic
+Cons --> UC2_Socratic : Drive Pathologic Inquiry Dialogue
+
+' Asynchronous Automated Verification Channel
+UC2_Socratic ..> UC2_BERT : Stream Conversation Tokens
+UC2_BERT ..> UC2_Referee : <<extend>> (Triggered on Impasse / Chat Hallucination)
+UC2_Referee ..> UC2_RAG_Fetch : <<include>>
+UC2_RAG_Fetch ..> UC2_Review : Inject Ground-Truth Evidence
+
+' Finalization Steps
+Rad --> UC2_Review
+Rad --> UC2_Finalize
+UC2_Finalize ..> UC2_Sync : <<include>>
+UC2_Sync --> EMR : POST Validated JSON Payload
+@enduml
+```
+
+![image.png](Q2%20Automation%20Override%20Risk%20(AI%20Correct%20Doctor%20Ove/image.png)

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/Q3 Clinician Subservience Risk (AI Hallucinates Do 378f910aea7580f8afb1c708eaf53e15.md

@@ -0,0 +1,69 @@
+# Q3: Clinician Subservience Risk
+(AI Hallucinates / Doctor Correct)
+
+Layered Three-Tier ML Stack Performance Impact (Your Proposed Design): The Objective Critic Loop initiates when a clinician contests an automated diagnostic grade, triggering an interactive Socratic consultation that bridges human intuition with machine inference via the VKIST-ML vision stack. During this loop, the LLM Explainer renders a GradCAM-anchored reasoning draft that visualizes the specific pixel-level feature activation logic, enabling the clinician to identify and isolate artifacts—such as motion tremors—that may have induced a system hallucination. To ensure diagnostic integrity, a BERT-based detector continuously monitors the dialogue for semantic drift, and if the interaction reaches an impasse or context hallucination is detected, the RAG-Referee intervenes as an unbiased, independent arbiter. By cross-verifying the clinician’s assertion and the model’s reasoning against raw imaging tensors and immutable, source-cited clinical guidelines (e.g., ESSR/OMERACT standards), the Referee resolves diagnostic ambiguity with objective evidence, ultimately committing the validated session as an annotated ground-truth record for targeted system reinforcement.
+
+```jsx
+@startuml
+' Layout optimizations to secure compact rendering and prevent image fragmentation
+skinparam linetype polyline
+skinparam packageStyle rectangle
+skinparam rectangle {
+    BackgroundColor #fefefe
+    BorderColor #555555
+}
+
+' Actors strictly mapped to match your canonical architectural definitions
+actor "Radiologist (UP5)" as Rad
+actor "Internal Consultor (LLM Chat)" as Cons <<System>>
+actor "System Maintainer" as Maint <<System>>
+
+rectangle "VKIST MSK Workspace - Q4 Architecture" {
+    
+    usecase "Evaluate Epistemic Uncertainty Gate" as UC4_Trigger
+    
+    rectangle "Socratic Workspace UI Panel" {
+        usecase "Shift to Clinical Investigation Mode" as UC4_Halt
+        usecase "Engage in Socratic Discussion" as UC4_Socratic
+        usecase "Render Manual Checklist Canvas" as UC4_Synth
+    }
+    
+    rectangle "Verification & Arbitration Kernel" {
+        usecase "Audit Chat Token Drift (BERT)" as UC4_BERT
+        usecase "Execute RAG-Referee Check" as UC4_Referee
+        usecase "Return Null-Match Signal" as UC4_RAG_Fetch
+    }
+    
+    rectangle "Clinical Resolution Gate" {
+        usecase "Document Novel Morphological Features" as UC4_Review
+        usecase "Authorize Serialized Anomaly Package" as UC4_Finalize
+    }
+    
+    usecase "Asynchronous Telemetry Queue Sync" as UC4_Sync
+}
+
+' Initial Data Intake and Uncertainty Routing Paths
+Rad --> UC4_Trigger : Feed OOD Image Tensors
+UC4_Trigger ..> UC4_RAG_Fetch : <<include>> (Triggers Empty Vector Result)
+UC4_RAG_Fetch ..> UC4_Halt : <<extend>> (On Zero-Match Guidelines + Low Conf Tensors)
+UC4_Halt ..> UC4_Synth : <<include>>
+
+' Direct Socratic Analysis Run-time Workspace
+Rad --> UC4_Socratic
+Cons --> UC4_Socratic : Drive Exploratory Morphology Dialogue
+
+' Live Guardrail and Exception Evaluation Paths
+UC4_Socratic ..> UC4_BERT : Stream Conversation Tokens
+UC4_BERT ..> UC4_Referee : <<include>> (Validates Logical Framing Stability)
+
+' Manual Audit, Documenting Anomaly and Consent Finalization
+Rad --> UC4_Review : Acknowledge Guideline Limitation
+Rad --> UC4_Finalize : Provide Native Opt-In Telemetry Consent
+
+' Async Data Serialization Sink to System Maintainer Ledger
+UC4_Finalize ..> UC4_Sync : <<include>>
+UC4_Sync --> Maint : POST Encrypted Tensors & Logs for Model Retraining
+@enduml
+```
+
+![image.png](Q3%20Clinician%20Subservience%20Risk%20(AI%20Hallucinates%20Do/image.png)

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/Q4 Double Blind Failure dues to edge-case (AI Faul 378f910aea7580618972f1583ab0e96b.md

@@ -0,0 +1,69 @@
+# Q4: Double Blind Failure dues to edge-case
+(AI Faulty / Doctor Biased)
+
+Layered Three-Tier ML Stack Performance Impact (Your Proposed Design): Anomaly Escalation Protocol: In instances where both the diagnostic system and the clinician encounter an edge-case—or "unknown-unknown"—that lacks precedent in the current RAG knowledge base, the system initiates the Anomaly Escalation Protocol. The LLM Explainer detects this "epistemic uncertainty" (via low vision-stack confidence and empty RAG retrieval results) and shifts the interface from "Diagnostic Support" to "Clinical Investigation Mode." Instead of attempting to force a Grade-based diagnosis, the Internal Consultor guides the clinician to document the unique morphological features through a structured annotation protocol, facilitating a Socratic investigation into the anomaly. The system transparently acknowledges the limitation, explicitly stating that current clinical guidelines do not cover this specific presentation, and prompts the clinician to manually document findings. With the clinician’s consent, the workspace commits this session as a "Novel Research Case," automatically serializing the raw imaging tensors, clinician observations, and artifact logs to a secure telemetry queue, flagging the data for system maintainers to perform targeted model retraining and protocol refinement.
+
+```jsx
+@startuml
+' Layout optimizations to secure compact rendering and prevent image fragmentation
+skinparam linetype polyline
+skinparam packageStyle rectangle
+skinparam rectangle {
+    BackgroundColor #fefefe
+    BorderColor #555555
+}
+
+' Actors strictly mapped to match your canonical architectural definitions
+actor "Radiologist (UP5)" as Rad
+actor "Internal Consultor (LLM Chat)" as Cons <<System>>
+actor "System Maintainer" as Maint <<System>>
+
+rectangle "VKIST MSK Workspace - Q4 Architecture" {
+    
+    usecase "Evaluate Epistemic Uncertainty Gate" as UC4_Trigger
+    
+    rectangle "Socratic Workspace UI Panel" {
+        usecase "Shift to Clinical Investigation Mode" as UC4_Halt
+        usecase "Engage in Socratic Discussion" as UC4_Socratic
+        usecase "Render Manual Checklist Canvas" as UC4_Synth
+    }
+    
+    rectangle "Verification & Arbitration Kernel" {
+        usecase "Audit Chat Token Drift (BERT)" as UC4_BERT
+        usecase "Execute RAG-Referee Check" as UC4_Referee
+        usecase "Return Null-Match Signal" as UC4_RAG_Fetch
+    }
+    
+    rectangle "Clinical Resolution Gate" {
+        usecase "Document Novel Morphological Features" as UC4_Review
+        usecase "Authorize Serialized Anomaly Package" as UC4_Finalize
+    }
+    
+    usecase "Asynchronous Telemetry Queue Sync" as UC4_Sync
+}
+
+' Initial Data Intake and Uncertainty Routing Paths
+Rad --> UC4_Trigger : Feed OOD Image Tensors
+UC4_Trigger ..> UC4_RAG_Fetch : <<include>> (Triggers Empty Vector Result)
+UC4_RAG_Fetch ..> UC4_Halt : <<extend>> (On Zero-Match Guidelines + Low Conf Tensors)
+UC4_Halt ..> UC4_Synth : <<include>>
+
+' Direct Socratic Analysis Run-time Workspace
+Rad --> UC4_Socratic
+Cons --> UC4_Socratic : Drive Exploratory Morphology Dialogue
+
+' Live Guardrail and Exception Evaluation Paths
+UC4_Socratic ..> UC4_BERT : Stream Conversation Tokens
+UC4_BERT ..> UC4_Referee : <<include>> (Validates Logical Framing Stability)
+
+' Manual Audit, Documenting Anomaly and Consent Finalization
+Rad --> UC4_Review : Acknowledge Guideline Limitation
+Rad --> UC4_Finalize : Provide Native Opt-In Telemetry Consent
+
+' Async Data Serialization Sink to System Maintainer Ledger
+UC4_Finalize ..> UC4_Sync : <<include>>
+UC4_Sync --> Maint : POST Encrypted Tensors & Logs for Model Retraining
+@enduml
+```
+
+![image.png](Q4%20Double%20Blind%20Failure%20dues%20to%20edge-case%20(AI%20Faul/image.png)

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/UC_CONTEXT.md

@@ -0,0 +1,282 @@
+# CONTEXT.md for the Usecase Discovery : FR-25
+
+- The requirement: FR-25 == ULTS-Đánh giá và phân cấp mức độ viêm màng hoạt dịch (Synovitis Grading)
+
+- Explain why the se should care on this usecase in the design process
+    - **The Gap:** Lợi ích kỹ thuật & Giá trị cốt lõi của Use Case Phân cấp Viêm màng hoạt dịch đối với Kiến trúc Phần mềm (Missing Clinical rationale vs. Engineering value optimization for Synovitis Grading).
+    - **The Question:** Tại sao quy trình lâm sàng chuẩn hóa này lại đảm bảo tính chính xác khi phân cấp (`Synovitis Grading`) và tại sao một Kỹ sư Phần mềm (SE) phải đặc biệt quan tâm đến Use Case này khi thiết kế sản phẩm?
+    - **The Hint:** Để xây dựng một sản phẩm Y tế (Healthcare AI Product) thành công, chúng ta không được coi Use Case này chỉ là một tính năng CRUD hay hiển thị ảnh đơn thuần. Hiểu rõ bản chất toán học/vật lý của quy trình giúp SE thiết kế cơ chế lưu trữ dữ liệu (Data Schema), cấu hình Pipeline xử lý ảnh AI và tối ưu hóa trải nghiệm UIX không bị lỗi logic giải phẫu.
+    - **The Recommendations:** Dưới đây là câu trả lời phân tích sâu dưới góc nhìn của một Kỹ sư Hệ thống / Lập trình viên:
+    
+    ### PHẦN 1: Tại sao quy trình này đảm bảo việc phát hiện và phân cấp chính xác? (Góc nhìn Data Pipeline & Signal Processing)
+    
+    Nếu coi cơ thể người là một hệ thống phần cứng và máy siêu âm là một module quét dữ liệu ngoại vi (Hardware Scanner), quy trình 6 bước lâm sàng chính là các điều kiện tiền đề để **đảm bảo tính toàn vẹn của tín hiệu (Signal Integrity)** và ngăn chặn **nhiễu dữ liệu (Data Corruption)**:
+    
+    1. **Khử nhiễu biên (Eliminating Boundary Noise - Bước 1):** việc gập đầu gối 20°–30° tương đương với việc thực hiện lệnh `Format / Standardize` bề mặt quét. Nó triệt tiêu hiện tượng *Bất đẳng hướng âm học (Acoustic Anisotropy)* – vốn là một dạng nhiễu tín hiệu vật lý khiến mô khỏe mạnh bị biến đổi thành các pixel đen giả lập tổn thương.
+    2. **Cố định Hệ tọa độ (Fixing Coordinate System - Bước 2):** Đặt đầu dò dọc (`Longitudinal`) giúp mô hình AI thu được một contract dữ liệu ảnh tĩnh có cấu trúc giải phẫu phân tầng rõ ràng (`Multi-layered Frame`). Đỉnh xương bánh chè hoạt động như một điểm mốc $X, Y = (0,0)$ cố định để hệ thống chạy Edge Detection chuẩn xác.
+    3. **Phân tích Đa luồng song song (Multi-threading Analytics - Bước 3 & 4):**
+        - **Luồng B-Mode (Cấu trúc Hình học):** Trích xuất độ dày mô (`float thickness_mm`) $\rightarrow$ Phản ánh dung lượng thiệt hại vật lý tĩnh (Structural Damage).
+        - **Luồng Power Doppler (Lưu lượng Biến động):** Trích xuất mật độ màu của dòng máu (`float vascular_percentage`) $\rightarrow$ Phản ánh lưu lượng dữ liệu thời gian thực đang chạy (Active Inflammation).
+    4. **Tránh lỗi nén hệ thống (Avoiding Signal Throttling):** Việc lướt nhẹ tay đầu dò (minimal pressure) giữ cho luồng truyền dẫn tín hiệu mạch máu không bị bóp nghẹt (Throttling), tránh việc hệ thống tính toán sai lệch điểm số hoạt tử/viêm mạch dẫn đến kết quả âm tính giả.
+    
+    ### PHẦN 2: Tại sao Kỹ sư Phần mềm (SE) phải đặc biệt quan tâm đến Use Case này?
+    
+    Từ góc nhìn sản phẩm và kiến trúc hệ thống của dự án `VKIST_ULTRASOUND`, đây không phải là một tính năng bổ sung, mà chính là **Core Core Business Logic (Lõi nghiệp vụ quyết định)** vì các lý do sau:
+    
+    ### 1. Định hình Data Model (Schema) cho toàn bộ hệ thống
+    
+    Nếu không hiểu quy trình này, bạn sẽ thiết kế cơ sở dữ liệu bị thiếu trường dữ liệu nghiêm trọng. Điểm số `Synovitis Grade` không thể lưu dưới dạng một trường `int grade` đơn giản. Dữ liệu y khoa chuẩn hóa bắt buộc phải là một đối tượng phức hợp (Compound Object Model):
+    
+    JSON
+    
+    ```
+    {
+      "patient_id": "BN-10023",
+      "scan_metadata": {
+        "joint": "KNEE",
+        "side": "RIGHT",
+        "plane": "suprapat-long",
+        "patient_flexion_degree": 25
+      },
+      "extracted_metrics": {
+        "synovial_thickness_mm": 4.2,
+        "power_doppler_area_percentage": 34.5
+      },
+      "severity_classification": {
+        "suggested_grade": 2,
+        "confirmed_grade": 2,
+        "is_overridden_by_doctor": false
+      }
+    }
+    ```
+    
+    ### 2. Kích hoạt State Machine & Pipeline xử lý của AI (Mô tả trong tài liệu VKIST)
+    
+    Theo tài liệu kiến trúc của hệ thống, Use Case này là điểm kết thúc (`Final Destination`) của một Pipeline phân nhánh phức tạp. Khi ảnh DICOM/Siêu âm được đẩy lên hệ thống:
+    
+    - **Mô hình 1 (ConvNeXt):** Kiểm tra góc chụp. Nếu và chỉ nếu kết quả trả về đúng `sup_up_long`, hệ thống mới kích hoạt State tiếp theo.
+    - **Mô hình 2 (EfficientNet/MedViT):** Kiểm tra trạng thái phân loại nhị phân `Has Inflammation = True/False`.
+    - **Mô hình 3 (MedSAM/UNet):** Tiến hành phân đoạn vùng ảnh (Segmentation) tạo Mask đè màu để tính toán diện tích pixel bị tổn thương, từ đó tự động map ra điểm số Phân cấp từ 0 đến 3.
+        
+        Nếu Use Case này bị lỗi hoặc UIX thiết kế không khớp, toàn bộ Pipeline AI trị giá hàng nghìn giờ huấn luyện phía sau sẽ mất hoàn toàn giá trị sử dụng thực tế.
+        
+    
+    ### 3. Giải quyết bài toán Tải trọng hệ thống và Kiệt sức lâm sàng (Clinical Exhaustion)
+    
+    Tại các bệnh viện công tuyến trung ương của Việt Nam (Bạch Mai, Bệnh viện E), một bác sĩ (UP5) phải xử lý >100 ca/ca trực.
+    
+    - Nếu không có phần mềm: Bác sĩ phải đổi ghế, chuyển ứng dụng, gõ tay kết quả vào hệ thống EMR thủ công $\rightarrow$ Nút thắt cổ chai gây delay hệ thống (Latency).
+    - Khi có Use Case này được tự động hóa trên Dashboard: AI tính toán diện tích, trả về gợi ý bậc viêm ngay trên canvas xem ảnh, bác sĩ chỉ mất đúng 1 click chuột để xác nhận và Sync tự động sang Database tổng. Bạn đang giúp bệnh viện giảm thời gian xử lý một ca từ 5 phút xuống còn 30 giây, trực tiếp tối ưu hóa thông lượng (Throughput) cho toàn bộ hạ tầng y tế.
+    - **The Alignment Check:** Với góc nhìn bóc tách hệ thống và phân tích Pipeline tín hiệu/AI như trên, bạn đã thấy rõ được bài toán kiến trúc mình cần giải quyết ở Use Case này chưa, hay có điểm nào cần làm sáng tỏ thêm trước khi chúng ta vẽ sơ đồ Use Case bằng PlantUML?
+- Explain Why doctor are caring so much on this usecase
+    - **The Gap:** Hiểu rõ động lực lâm sàng và giá trị chẩn đoán thực tế của Bác sĩ (Missing Clinical Drivers and Real-World Diagnostic Insights for Synovitis Grading).
+    - **The Question:** Tại sao Bác sĩ Chẩn đoán hình ảnh (UP5) lại đặc biệt quan tâm đến Use Case Phân cấp Viêm màng hoạt dịch (`Synovitis Grading`), và chỉ số này tiết lộ điều gì cốt lõi trong hành trình chẩn đoán, điều trị của bệnh nhân?
+    - **The Hint:** Trong y khoa, bản thân hình ảnh siêu âm xám chỉ là dữ liệu thô (raw data). Kết quả phân cấp từ Use Case này chính là **thông tin có cấu trúc (structured insights)** giúp bác sĩ trả lời câu hỏi cốt lõi của lâm sàng: Bệnh nhân này đang bị tàn phá khớp ở mức độ nào, tổn thương này là mạn tính (sẹo mô) hay cấp tính (đang bùng phát), và phác đồ điều trị bằng thuốc hoặc can thiệp ngoại khoa nào là chính xác nhất.
+    - **The Recommendations:** Dưới đây là bóc tách chi tiết lý do vì sao bác sĩ cần Use Case này, được phân tích rõ ràng để một Kỹ sư Phần mềm nắm bắt trọn vẹn nghiệp vụ (Domain Knowledge):
+    
+    ### 1. Phân biệt Giữa "Tổn thương Cũ" (Mạn tính) và "Đợt Viêm Cấp" (Đang bùng phát)
+    
+    - **Ý nghĩa lâm sàng:** Khi nhìn vào ảnh siêu âm đen trắng (B-mode), bác sĩ thấy một vùng màng hoạt dịch dày lên (ví dụ: dày 4mm). Tuy nhiên, ảnh đen trắng đơn thuần **không thể** cho biết vùng phì đại đó là vết sẹo cũ từ 3 năm trước (mô xơ đã ổn định) hay là vùng mô đang liên tục sưng tấy, ăn mòn sụn khớp.
+    - **Use Case tiết lộ điều gì:** Bằng cách kết hợp luồng dữ liệu của **Power Doppler**, Use Case này bóc tách và định lượng chính xác mật độ mạch máu tăng sinh (`Hypervascularity`).
+        - *Dày mô + Không có tín hiệu Doppler (Grade 1):* Tổn thương cũ, chỉ cần theo dõi hoặc vật lý trị liệu.
+        - *Dày mô + Tín hiệu Doppler dày đặc (Grade 3):* Ổ viêm đang hoạt động cực kỳ dữ dội. Hệ thống miễn dịch của bệnh nhân đang tấn công nhầm vào chính các tế bào khớp gối, giải phóng hàng loạt enzyme ăn mòn sụn và xương. Bác sĩ cần phải can thiệp ngay lập tức bằng thuốc ức chế miễn dịch mạnh (như Corticoid hoặc DMARDs) để chặn đứng dòng thác phá hủy này.
+    
+    ### 2. Điểm Số Quyết Định Phác Đồ Điều Trị (Actionable Clinical Metric)
+    
+    Điểm số Phân cấp từ 0 đến 3 không phải là một cái tag hiển thị cho đẹp, nó hoạt động giống như một **luồng điều hướng logic (Decision Tree)** quyết định trực tiếp hành động lâm sàng của bác sĩ:
+    
+    - **Grade 0 (Bình thường):** Chuyển bệnh nhân sang chế độ phòng ngừa, xuất viện.
+    - **Grade 1 (Nhẹ):** Chỉ định điều trị nội khoa bảo tồn ở mức độ thấp (Dùng thuốc kháng viêm không Steroid - NSAIDs, thay đổi lối sống, tập vật lý trị liệu với bác sĩ PT - UP6).
+    - **Grade 2 (Vừa):** Cân nhắc tiêm thuốc nội khớp (tiêm Corticoid trực tiếp vào ngách khớp gối để dập dịch viêm tại chỗ) kết hợp điều trị thuốc đặc hiệu.
+    - **Grade 3 (Nặng/Nghiêm trọng):** Rút dịch khớp (Arthrocentesis) để giảm áp lực, chỉ định nhập viện điều trị tích cực, hoặc chuyển tuyến ngoại khoa để thực hiện phẫu thuật nội soi cắt màng hoạt dịch (Synovectomy) nhằm cứu lấy sụn khớp trước khi gối bị biến dạng hoàn toàn không thể phục hồi.
+    
+    ### 3. Thước Đo Khách Quan Để Đánh Giá Hiệu Quả Thuốc (Treatment Monitoring Dashboard)
+    
+    - **Nỗi đau của Bác sĩ:** Khi điều trị các bệnh tự miễn như Viêm khớp dạng thấp, bệnh nhân phải uống thuốc ròng rã nhiều tháng trời. Nếu bác sĩ chỉ hỏi bệnh nhân *"Bác có bớt đau không?"*, câu trả lời sẽ cực kỳ chủ quan và không chính xác (do ngưỡng chịu đau của mỗi người khác nhau và có hiệu ứng giả dược).
+    - **Use Case tiết lộ điều gì:** Use Case này cung cấp một **Standardized Baseline (Mốc chuẩn hóa)** để so sánh liên tục qua các mốc thời gian (Time-series Analysis).
+        - *Tháng 1:* Bệnh nhân đến khám $\rightarrow$ Hệ thống chấm **Grade 3** (Màng hoạt dịch dày 6mm, Doppler phủ 65% area).
+        - *Tháng 3 (Sau 2 tháng uống thuốc):* Bệnh nhân tái khám $\rightarrow$ Hệ thống chấm **Grade 1** (Màng hoạt dịch giảm còn 2.5mm, Doppler chỉ còn vài chấm cô lập).
+            
+            $\rightarrow$ Phần mềm tiết lộ cho bác sĩ một bằng chứng số liệu toán học tuyệt đối: **Phác đồ thuốc hiện tại đang hoạt động hiệu quả**, tiếp tục duy trì liều lượng. Ngược lại, nếu điểm số vẫn là Grade 3, hệ thống cảnh báo bác sĩ rằng bệnh nhân đang kháng thuốc, phải đổi sang loại thuốc sinh học đắt tiền hơn ngay lập tức.
+            
+    
+    ### 4. Triệt Tiêu Biến Thiên Giữa Các Bác Sĩ (Eradicating Inter-observer Variability)
+    
+    - **Thực trạng tại bệnh viện:** Việc phân cấp siêu âm thủ công phụ thuộc rất nhiều vào mắt nhìn chủ quan và kinh nghiệm của từng người. Bác sĩ A (15 năm kinh nghiệm) nhìn ảnh đoán là Grade 2, nhưng Bác sĩ B (mới ra trường 1 năm) lại chấm là Grade 3 vì thấy túi dịch có vẻ to. Sự lệch pha này gây nguy hiểm cho tính đồng nhất của phác đồ điều trị.
+    - **Use Case tiết lộ điều gì:** Khi có AI hỗ trợ trích xuất độ dày vùng ngách trên xương bánh chè (`suprapatellar recess`) và tính tỷ lệ pixel màu Doppler một cách tự động, hệ thống đóng vai trò như một **bộ kiểm tra điều kiện logic khách quan (Deterministic Gatekeeper)**. Nó đưa ra một mức điểm gợi ý dựa trên thuật toán tính toán diện tích chuẩn y khoa, giúp đồng bộ hóa chất lượng chẩn đoán tại bệnh viện. Bác sĩ dù già hay trẻ đều nhìn thấy một cơ sở số liệu minh bạch để đưa ra quyết định cuối cùng.
+    - **The Alignment Check:** Qua bóc tách dưới góc nhìn lâm sàng này, bạn đã hiểu vì sao kết quả đầu ra của Use Case này (`Grade 0-3`) lại đóng vai trò là "trái tim mạch máu" cho toàn bộ Dashboard điều trị phía sau chưa, hay bạn muốn chúng ta đào sâu thêm vào điểm nào trước khi thiết kế các tương tác UIX?
+- The System suggest what currently being missed from FR and need to define in the UC:
+    - **The Gap:** Ambiguous System & Actor Interaction Boundaries inside the Grading Workflow (Thiếu tường minh về ranh giới tương tác giữa Hệ thống và Bác sĩ).
+    - **The Question:** How exactly should the doctor **interact** with the system's automated AI calculation when adjusting or validating the suggested severity score (e.g., from Grade 2 to Grade 3)? - The answer of this
+        
+        The precise, clinically accurate baseline workflow executed by a Diagnostic Radiologist (UP5) consists of the following 6 sequential phases:
+        
+        - **Step 1 (Patient Posture Standardization):** The clinician places the patient in a supine position with the target knee supported by a bolster in **20°–30° of slight flexion**. This stretches the extensor mechanism (the **Quadriceps/Patellar Tendon)** and eliminates diagnostic tracking errors caused by acoustic anisotropy.
+            - Explain with simplification for Software Engineer
+                - **The Clinical Action:** The patient lies flat, knee bent exactly 20°–30° over a cushion.
+                - **The Software Engineer Analogy:** **Setting up consistent environment variables and running an initialization handshake.**
+                - **Deep Jargon Breakdown:**
+                    - **Extensor Mechanism - Quadriceps/Patellar Tendon:** Think of this as a mechanical rubber band system (quadriceps muscle → tendon →kneecap → shin bone). When the leg is completely straight, this system sags and wrinkles. Bending it 20°–30° stretches it taut, creating a flat, predictable surface line.
+                    - **Acoustic Anisotropy (The Crucial Hardware Bug):** This is a structural physical hardware limitation of ultrasound waves. If the sound beam hits a tendon at a perfect 90° right angle, it bounces back bright white (**Echoic**). If the probe tilts even 5° offline because the tendon is curved/sagging, the wave scatters sideways, and the tissue suddenly registers on-screen as pitch black (**Hypoechoic**), mimicking a fake fluid tear or inflammatory lesion.
+                - **Why this matters for your UI/Product Design:** This step is your raw input data sanity check. If the patient isn't positioned right, the ultrasound picture is filled with visual artifact bugs (garbage in, garbage out). Your system needs to know it is processing a standardized 20°–30° landscape view.
+        - **Step 2 (Longitudinal Probe Alignment):** The clinician positions a high-frequency linear transducer probe over the midline of the **suprapatellar recess** (sagittal plane), aligning the distal edge over the upper pole of the patella to capture the clear multi-layered layout of the quadriceps tendon.
+            - Explain with simplification for SE
+                - **The Clinical Action:** The linear probe is placed lengthwise right down the middle of the upper knee, overlapping the top edge of the kneecap.
+                - **The Software Engineer Analogy:** **Pointing your API client path to the exact parent database index to unpack a nested multi-layered object arrays.**
+                - **Deep Jargon Breakdown:**
+                    - **Suprapatellar Recess:** This is the precise target memory location—a pouch-like joint cavity hiding right above the kneecap (**Supra** = above, **Patella** = kneecap) underneath the deep tissue layers.
+                    - **Sagittal Plane:** A vertical front-to-back cross-section cut. If your application was a 3D video game engine, this is viewing the joint asset precisely from the orthogonal **Side View Viewport**, rather than looking from the front or top down.
+                - **Why this matters for your UI/Product Design:** This gives the system its coordinate system reference frame. In this view, your AI algorithm can run edge detection along standard anatomical landmarks, treating the top edge of the patella as a rock-solid structural zero-point anchor on a 2D canvas.
+        - **Step 3 (B-Mode Structural Metric Capture):** Using standard Grey Scale (B-mode), the radiologist identifies the hypoechoic tissue area resting between the *prefemoral fat pad* and the *suprapatellar fat pad*. They visually calculate the maximum vertical distance of joint capsule distension/thickening using the ultrasound console's physical calipers.
+            - Explain for SE
+                - **The Clinical Action:** The doctor switches to a black-and-white image, identifies the space between two fat patches, and hits two points on the console to calculate the space thickness.
+                - **The Software Engineer Analogy:** **Running a 2D Bounding Box Segmentation model to extract a quantitative `float` metric (distance in mm) between two fixed system nodes.**
+                - **Deep Jargon Breakdown:**
+                    - **B-Mode (Brightness Mode):** This is the baseline structural image format. It transforms reflected sound wave amplitudes into live pixel intensity map arrays (high reflection = white pixels; zero reflection/fluid fluid pools = dark black pixels).
+                    - **Hypoechoic Tissue Area:** Any region that absorbs or passes sound waves easily instead of reflecting them, rendering as a dark grey or black signal pool. Inflamed synovial tissue fluid sits in this category.
+                    - **Prefemoral & Suprapatellar Fat Pads:** These are your permanent upper and lower hardware guardrail markers. The suprapatellar pouch sits wedged right between them like an expandable buffer queue.
+                - **Why this matters for your UI/Product Design:** This is **REQ-RAD-02** in your requirement documentation. The doctor uses manual calipers to measure this space. Your product UI can introduce a digital bounding path box or automated point-to-point drawing tool overlay to automatically extract this distance variable, completely stripping away the manual console math step.
+        - **Step 4 (Power Doppler Vascularity Mapping):** The clinician activates the Power Doppler mode on the console, optimizing the wall filter and PRF settings. They carefully hover the probe with **minimal contact pressure** to avoid compressing low-velocity synovial capillaries, visually counting or calculating the percentage area occupied by active blood flow signals inside the suprapatellar landscape.
+            - Explain for SE
+                - **The Clinical Action:** The doctor switches on the color overlay feature, tweaks the sensitivity filters, and hovers the probe extremely lightly without pressing down into the skin.
+                - **The Software Engineer Analogy:** **Activating a live telemetry tracer module with a low-pass noise filter to map active server data traffic volume while avoiding an external physical choke/throttling event.**
+                - **Deep Jargon Breakdown:**
+                    - **Power Doppler Mode:** A specialized signal tracking sub-routine. Instead of mapping structural tissue borders, it tracks shifts in frequency caused by moving targets (red blood cells). It highlights these regions with bright, glowing color maps overlaid right on top of the black-and-white structural layer.
+                    - **Wall Filter & PRF (Pulse Repetition Frequency):** These are variable noise gates. If configured wrong, minor hand tremors will bleed into the visual feed as massive colored pixels (**Clutter Artifact Noise**).
+                    - synpvia Capillary Compression Edge Case: If the doctor applies heavy hand force, they manually flatten the tiny micro-blood vessels inside the knee. This physically blocks blood flow, wiping out the signal completely on screen and returning a false negative trace.
+                - **Why this matters for your UI/Product Design:** This maps directly to your **Hypervascularity parameter**. Your interface can assist by calculating the ratio of bright color pixels to the total area of the segmented pouch, converting a subjective visual guess into a precise numerical percentage readout.
+        - **Step 5 (Semi-Quantitative Grade Synthesis):** The clinician combines both structural metrics mentally against standard musculoskeletal classification tiers: - THE VKIST ML-Module current stop in here
+            - *Grade 0 (None):* Completely flat layers; no hypoechoic separation or vascular flow signals.
+            - *Grade 1 (Mild):* Thin hypoechoic line running parallel to the femoral bone path; single or minimal isolated vascular blood flow spots.
+            - *Grade 2 (Moderate):* Evident hypoechoic expansion pushing the fat pads apart, but lines remain flat; active vascular flow spots occupying less than 50% of the calculated synovial area.
+            - *Grade 3 (Severe):* Clear convex or distinct bulging capsule distortion extending outward; intense confluent flow signals covering more than 50% of the calculated synovial landscape.
+            - Explain for SE
+                - **The Clinical Action:** The doctor looks at both parameters (the pouch thickness + the active color blood flow maps) and maps them to a standard clinical severity tier level (0 to 3).
+                - **The Software Engineer Analogy:** **Evaluating raw aggregated metric values against a core business logic conditional switch block (`switch(severityGrade)`) to determine system status codes.**
+                - **Deep Tiers Demystified via Code Logic:**
+                    - **Grade 0 (Healthy Baseline):**
+                        
+                        ```jsx
+                        if (synovialThickness === 0 && hypervascularityScore === 0) return "Grade 0: Normal Space";
+                        ```
+                        
+                    - **Grade 1 (Mild Inflammation):** Space is filled with a thin, parallel line of tissue expansion; trace color dots show up.JavaScript
+                        
+                        ```
+                        if (synovialThickness > 0 && hypervascularityScore <= 0.10) return "Grade 1: Mild Distension";
+                        ```
+                        
+                    - **Grade 2 (Moderate Inflammation):** The tissue swells enough to visibly push the flanking fat pads apart, and the active blood flow color blocks cover up to half of the pouch container zone.JavaScript
+                        
+                        ```
+                        if (synoviumDistended === true && hypervascularityScore < 0.50) return "Grade 2: Moderate Pouch Deflection";
+                        ```
+                        
+                    - **Grade 3 (Severe Inflammation):** The pouch balloons into a curved, outward bulging geometric form; intense, connected color maps take over more than half of the space landscape.JavaScript
+                        
+                        ```
+                        if (capsuleShape === 'convex_bulge' || hypervascularityScore >= 0.50) return "Grade 3: Critical Structural Flare";
+                        ```
+                        
+        - **Step 6 (Manual Multi-Silo Transcription):** The clinician freezes the optimal reference frames on the hardware console, manually assigns a final severity index label, moves away from the ultrasound machine hardware screen to a desktop workstation PC, and types out the structural text variables into the hospital's Electronic Medical Record (EMR) text block.
+            - Explain for SE
+                - **The Clinical Action:** The doctor freezes the machine display screen, manually records a final tier index number, stands up, switches chairs to a secondary office computer, logs in, and re-types the exact observations by hand into a text window box.
+                - **The Software Engineer Analogy:** **A total lack of system database synchronization. Hand-copying raw log data variables from a separate terminal window and typing them line-by-line into a separate decoupled microservice application.**
+                - **Why this matters for your UI/Product Design:** This is the massive core workflow bottleneck. The goal of your upcoming workspace design is to build an interactive, unified web interface bridge. The AI processes the image data parameters natively, renders an automated classification tag proposal directly inside the primary viewing frame, and updates the shared patient record database with 0 manual transcript entries or physical context-switching loops.
+    - Additional - from the answer in the `Question` we can model the planUML code solution
+        
+        !image.png
+        
+        ```jsx
+        @startuml
+        ' Settings
+        left to right direction
+        skin rose
+        
+        ' Actors
+        actor "Diagnostic Radiologist (UP5)" as Rad
+        actor "Hospital EMR System" as EMR << System >>
+        actor "VKIST AI Pipeline" as AI << System >>
+        
+        ' System Boundary
+        rectangle "VKIST MSK Workspace - Synovitis Grading Engine" {
+            
+            ' Core Viewing & Extraction Use Cases
+            usecase "Load Patient Ultrasound Session" as UC-48376
+            usecase "Extract Joint Tissue Metrics" as UC_Extract
+            
+            ' AI Suggestion Processing
+            usecase "Compute Automated Severity Suggestion" as UC_AI_Compute
+            usecase "Display Suggestion Tag & Canvas Overlays" as UC_Display
+            
+            ' Clinician Interaction & Decision Loop
+            usecase "Review Suggested Synovitis Grade (0-3)" as UC-47988
+            usecase "Manually Override Severity Grade" as UC_Override
+            usecase "Sign & Finalize Diagnostic Conclusions" as UC-92006
+            
+            ' Data Sync Hand-off
+            usecase "Synchronize Patient Record" as UC_Sync
+        }
+        
+        ' Relationships & Flow Boundaries
+        Rad --> UC-48376
+        Rad --> UC-47988
+        Rad --> UC-92006
+        
+        ' AI Pipeline Interactions
+        UC-48376 ..> UC_Extract : <<include>>
+        UC_Extract --> AI : Transmit raw image streams
+        AI --> UC_AI_Compute : Process thickness & Doppler maps
+        UC_AI_Compute ..> UC_Display : <<include>>
+        
+        ' Review and Override Loop
+        UC_Display ..> UC-47988 : <<include>>
+        UC_Override .up.> UC-47988 : <<extend>> (If clinician disagrees with AI)
+        Rad --> UC_Override
+        
+        ' Finalization and Sync Hand-offs
+        UC-92006 ..> UC_Sync : <<include>>
+        UC_Sync --> EMR : Push standardized JSON structural data
+        @enduml
+        ```
+        
+    
+    → For the Synovist Grading the interaction between the clinician & system may occur 4 potential case: —> 4 possible interactions
+    
+    ```jsx
+    +-----------------------------------------------------------------------+
+    |                       HUMAN-AI CONCURRENT STATES                      |
+    +-----------------------------------+-----------------------------------+
+    |            QUADRANT 2             |            QUADRANT 1             |
+    |   Automation Override Risk        |          True Agreement           |
+    |                                   |                                   |
+    |   AI: Grade 3 (Accurate)          |   AI: Grade 2 (Accurate)          |
+    |   Human: Grade 1 (Oversight)      |   Human: Grade 2 (Confident)      |
+    |   Risk: Severe Disease Missed     |   Risk: None (Happy Path)         |
+    +-----------------------------------+-----------------------------------+
+    |            QUADRANT 4             |            QUADRANT 3             |
+    |       Double-Blind Failure        |    Clinician Subservience Risk    |
+    |                                   |                                   |
+    |   AI: Grade 2 (Boundary Error)    |   AI: Grade 3 (Hallucinated)      |
+    |   Human: Grade 1 (Biased Error)   |   Human: Grade 1 (Accurate)       |
+    |   Risk: Cascading System Error    |   Risk: Over-treatment Danger     |
+    +-----------------------------------+-----------------------------------+
+    ```
+    
+    THE ML-stack use in this scenarios: 
+    
+    - the grading ML-stack (VKIST-model) → always use (it’s the machine process on the raw-signal from device)
+    - the LLM Critic & Actor for acting as explainer on the results of the grading stack (de-blackbox) + conversation with the clinics for pathologic analysis <with RAG> + critic-suggestion  (this LLM shall have to loaded with SKILL / multi-agent system)
+    - the LLM-RAG-Referee for prevent bias & blindness of both-side (actor & grader & clinical)
+        
+        
+        | **Referee Role** | **Problem Solved** | **Mechanism** |
+        | --- | --- | --- |
+        | **1. Unbiased Arbiter** | **Conflict & Bias:** Prevents the LLM from hallucinating to match the clinician's incorrect bias (Confirmation Bias). | Operates as a **Session-State Arbiter**: It ignores conversation history and focuses purely on comparing the raw metrics (`GradCAM maps`, `Doppler indices`) against clinical definitions. |
+        | **2. Domain Guardian** | **Knowledge Obsolescence:**Prevents the system from using outdated medical standards (e.g., guidelines from 2020 instead of 2025). | Operates as a **Knowledge-Retrieval Guardian**: It triggers when the system detects high semantic entropy, fetching the *latest* approved academic guidelines to ensure all explanations remain clinically valid. |
+    
+    The Actor:
+    
+    - the UP-5 user working with the hardware
+    
+    4 scenarios can consider

proj_level_reading/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/update_uc_ids.py

@@ -0,0 +1,28 @@
+
+mapping = {
+    'UC_Load': 'UC-48376',
+    'UC_Review': 'UC-47988',
+    'UC_Finalize': 'UC-92006',
+    'UC_Q1_Explain': 'UC-25776',
+    'UC_Q1_Log': 'UC-02423',
+    'UC_Q2_Intercept': 'UC-22159',
+    'UC_Q2_Socratic': 'UC-55146',
+    'UC_Q2_BERT': 'UC-74821',
+    'UC_Q2_Arbiter': 'UC-65473',
+    'UC_Q3_Expose': 'UC-25637',
+    'UC_Q3_Isolate': 'UC-60739',
+    'UC_Q3_Commit': 'UC-62864',
+    'UC_Q4_Escalate': 'UC-35956',
+    'UC_Q4_Annotate': 'UC-47796',
+    'UC_Q4_Queue': 'UC-01580'
+}
+
+# file_path = '/Users/davestran/Downloads/vkist_internship/PILOT_PROJECT/Reading_docs/Requirement_Analysis/UC_Design/FR_25_UC_DESIGN/FR_25_UC_SPEC.md'
+# with open(file_path, 'r') as f:
+#     content = f.read()
+
+# for old, new in mapping.items():
+#     content = content.replace(old, new)
+
+# with open(file_path, 'w') as f:
+#     f.write(content)