silent-platform

byGitmushtaq

We are building a product called PulseVision. This is a full-stack AI-powered healthcare platform that helps users understand medical reports and take real-world action. 🧠 CORE VISION PulseVision converts: πŸ‘‰ Medical Report β†’ Insight β†’ Decision β†’ Action β†’ Follow-up We are NOT building a diagnosis system. We are building a: πŸ‘‰ Health Decision & Navigation Platform 🎯 PRIMARY USER FLOW A user should be able to: Upload a medical report (PDF/image) System analyzes it Get simplified explanation Understand risk level Get doctor recommendation See nearby hospitals Take action (call / navigate) Save and return later πŸ—οΈ SYSTEM ARCHITECTURE FRONTEND Framework: React (Vite) Styling: Tailwind CSS Routing: React Router Pages: Dashboard Upload Screen Analysis Progress Screen Results Screen Saved Reports BACKEND Framework: FastAPI (Python) Structure: backend/ β”œβ”€β”€ main.py β”œβ”€β”€ routes/ β”œβ”€β”€ services/ β”œβ”€β”€ utils/ └── models/ AI / PROCESSING LAYER OCR (basic for now) Text parsing Rule-based risk detection Doctor recommendation engine 🧩 CORE FEATURES 1. REPORT UPLOAD Accept PDF / Image Validate file Send to backend 2. OCR + ANALYSIS Backend should: Extract text Identify key values (LDL, sugar, hemoglobin) Normalize values Detect abnormalities 3. RISK ENGINE Output: Risk level: Low / Medium / High Confidence score 4. DECISION ENGINE Map: Biomarkers β†’ Doctor type Example: High cholesterol β†’ Cardiologist Low hemoglobin β†’ General physician 5. RESULTS OUTPUT Frontend should display: Summary (simple language) Risk level Doctor recommendation Detected values Confidence 6. HOSPITAL INTEGRATION Use: Google Maps Places API Fetch: Nearby hospitals Rating Distance Address Phone number 7. ACTION SYSTEM User should: Call hospital (open dialer) Open map (Google Maps) 8. SAVE & RETURN Save report Reopen later Resume action 9. ANALYTICS Track: Upload success Analysis success CTA clicks Call clicks Map clicks Save β†’ return β†’ action πŸ”„ FRONTEND FLOW Step 1: Dashboard Overview Recent reports β€œNew Analysis” button Step 2: Upload Drag & drop File preview Upload button Step 3: Progress Show steps: Reading report Extracting data Analyzing Generating result Step 4: Results Show: Risk level Doctor Next steps Hospital list CTA button Save option πŸ”Œ API DESIGN POST /upload Input: file Output: job_id GET /analyze/{job_id} Output: { "summary": "", "risk_level": "High", "doctor": "Cardiologist", "confidence": 0.85, "detected_values": [] } GET /hospitals/nearby Input: latitude longitude specialty Output: list of hospitals ⚠️ IMPORTANT RULES Do NOT overcomplicate Do NOT use heavy ML models initially Use rule-based logic first Keep UI clean and professional Keep frontend and backend modular πŸš€ DEVELOPMENT PHASES Phase 1: MVP UI screens Mock data Basic flow Phase 2: Real Integration Backend connection OCR Real hospital API Real actions Phase 3: Advanced Better AI models Personalization Notifications Health tracking πŸ“¦ FINAL DELIVERABLE A working system where: User uploads report Gets analysis Sees hospitals Takes action 🎯 END GOAL This should feel like: πŸ‘‰ A real product πŸ‘‰ Not a prototype πŸ‘‰ Not a demo

DashboardSaved ReportsProgress
Dashboard

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Dashboard design preview
Dashboard: View Overview
Upload: Select Report
Upload: Submit File
Progress: Track Analysis
Results: View Risk Level
Results: View Doctor Recommendation
Results: Browse Hospitals
Results: Call or Navigate
Saved Reports: Save Report
Saved Reports: Reopen Report