D.O.C is an intelligent medication companion that helps patients manage their medications safely through AI-powered drug identification, age verification, dosage confirmation, and comprehensive health documentation.

• 40% of medication errors are age-related
• 7,000+ annual deaths from preventable medication mistakes
• Patients don't know if their medications are safe for their age
• No centralized system to track medications, documents, and doctor communications
• Terminal illness patients lack access to latest drug research

D.O.C provides 7 intelligent features:

1. Camera Drug Scanner - Identify drugs via photo, get instant descriptions
2. Side Effects Checker - Comprehensive side effect database
3. Age Verification - AI validates drug safety for patient's age
4. Dosage Confirmation - Verify prescribed dosage accuracy
5. Medical Triage - Store documents, prescriptions, doctor contacts
6. Research Updates - Latest drug news for cancer/terminal illnesses
7. Patient Logging - Voice/text notes sent directly to doctors

Unique Feature: Handles multiple medications simultaneously

• Framework: React 18 + Vite
• Styling: Tailwind CSS
• State Management: Context API + React Query
• Routing: React Router v6
• HTTP Client: Axios
• Camera: react-webcam
• Voice Recording: react-media-recorder

• Framework: FastAPI (Python 3.11+)
• Database: Supabase (PostgreSQL)
• Authentication: JWT tokens
• File Storage: Supabase Storage
• API Documentation: Swagger/OpenAPI

• OCR: Tesseract, Google Cloud Vision API
• NLP: Claude API (Anthropic), OpenAI Whisper
• Drug Data: OpenFDA, RxNorm, DrugBank
• Research: PubMed API, ClinicalTrials.gov API

Node.js 18+ Python 3.11+ Git Tesseract OCR

Quick Start

1. Clone Repository

• git clone https://github.com/Contractor-x/D.O.C/tree/Collins
• cd D.O.C

2. Frontend Setup

• cd frontend
• npm install
• cp .env.example .env

• npm run dev

3. Backend Setup

• cd backend
• python -m venv venv
• source venv/bin/activate

• pip install -r requirements.txt
• cp .env.example .env

• uvicorn app.main:app --reload

4. AI Services Setup

• cd ai-services
• pip install -r requirements.txt
• cp .env.example .env

• python -m ocr.drug_ocr # Test OC

• VITE_API_BASE_URL=http://localhost:8000/api/v1
• VITE_SUPABASE_URL=your_supabase_url
• VITE_SUPABASE_ANON_KEY=your_supabase_key

• DATABASE_URL=postgresql://user:pass@localhost:5432/doc
• SUPABASE_URL=your_supabase_url
• SUPABASE_KEY=your_supabase_key
• SECRET_KEY=your_jwt_secret_key
• CLAUDE_API_KEY=your_claude_api_key
• OPENAI_API_KEY=your_openai_key
• GOOGLE_CLOUD_VISION_KEY=your_google_vision_key

• OPENFDA_API_KEY=not_required
• RXNORM_API_KEY=not_required
• PUBMED_API_KEY=your_pubmed_key
• CLAUDE_API_KEY=your_claude_api_key
• OPENAI_API_KEY=your_openai_key

Authentication POST /api/v1/auth/register POST /api/v1/auth/login POST /api/v1/auth/refresh GET /api/v1/auth/me Camera & Drug Identification POST /api/v1/camera/scan GET /api/v1/drugs/{drug_id} POST /api/v1/drugs/identify POST /api/v1/drugs/batch-scan Side Effects GET /api/v1/side-effects/{drug_id} GET /api/v1/side-effects/interactions POST /api/v1/side-effects/report Age Verification POST /api/v1/age-verification/check GET /api/v1/age-verification/beers-criteria POST /api/v1/age-verification/batch-check Dosage Confirmation POST /api/v1/dosage/verify POST /api/v1/dosage/calculate GET /api/v1/dosage/guidelines/{drug_id} Medical Triage POST /api/v1/triage/documents/upload GET /api/v1/triage/documents DELETE /api/v1/triage/documents/{id} POST /api/v1/triage/doctors GET /api/v1/triage/doctors PUT /api/v1/triage/doctors/{id} Research Updates GET /api/v1/research/latest GET /api/v1/research/by-illness/{illness} POST /api/v1/research/bookmark GET /api/v1/research/bookmarks Patient Logging POST /api/v1/logs/text POST /api/v1/logs/voice GET /api/v1/logs POST /api/v1/logs/send-to-doctor GET /api/v1/logs/analytics

User Journey Login → Dashboard → Camera Scanner → Results → Side Effects → Age Verification → Dosage Check → Save to Triage → Log Experience Page Descriptions

1. Camera Scanner Live camera feed Capture multiple drugs at once OCR processing indicator Drug identification results Brief description for each drug
2. Side Effects List all identified drugs Expandable side effect cards Severity indicators (mild/moderate/severe) Interaction warnings Filter by severity
3. Age Verification Input patient age AI analyzes each drug for age-appropriateness Risk score (0-10) Recommendations Alternative suggestions
4. Dosage Confirmation Display prescribed dosage Compare with recommended dosage Show acceptable range Flag over/under dosing Doctor's prescription view
5. Medical Triage Upload medical documents (PDF, images) Document categorization (prescriptions, lab results, etc.) Doctor contact management Emergency contacts Quick access to recent documents
6. Research Updates Filter by illness type Latest clinical trials New drug approvals Research summaries Bookmark articles Share with doctor
7. Patient Logging Text entry for notes Voice recording option Categorize logs (side effects, mood, pain level) Timeline view Send specific logs to doctor AI analysis of patterns

1. OCR Drug Identification Technology: Tesseract + Google Cloud Vision Accuracy: 92%+ Process: Image preprocessing (grayscale, denoise, contrast) Text extraction Drug name matching with fuzzy logic NDC barcode detection
2. Age Risk Detection Algorithm: Custom ML + Beers Criteria Input: Drug name, dosage, patient age Output: Risk score (0-10), recommendations Rules: 40+ Beers Criteria drugs for elderly (65+) Pediatric contraindications (<18) Weight-based dosing for children Renal function adjustments
3. Side Effect Prediction Data Source: OpenFDA Adverse Events Model: Classification + NLP Features: Common vs rare side effects Severity classification Drug-drug interactions Food-drug interactions
4. Dosage Validation Algorithm: Rule-based + ML Checks: Age-appropriate dosing Weight-based calculations (mg/kg) Renal dose adjustments Maximum daily limits Frequency validation
5. Voice Transcription Technology: OpenAI Whisper API Languages: 90+ supported Features: Real-time transcription Medical terminology recognition Speaker diarization Sentiment analysis
6. Research Aggregation Sources: PubMed, ClinicalTrials.gov, FDA Algorithm: NLP + Content Ranking Features: Relevance scoring Publication date weighting Clinical trial phase filtering Automatic summarization
7. AI Explanations Technology: Claude API (Anthropic) Purpose: Patient-friendly explanations Reading Level: 8th grade Languages: English, Spanish (expandable)

Tables users id, email, password_hash, age, created_at medications id, user_id, drug_name, dosage, ndc_code, identified_at side_effects id, drug_id, effect_name, severity, frequency age_checks id, user_id, medication_id, age, risk_score, safe, checked_at dosage_checks id, medication_id, prescribed_dose, recommended_dose, within_range documents id, user_id, file_url, document_type, uploaded_at doctor_contacts id, user_id, doctor_name, specialty, phone, email research_articles id, title, summary, illness_type, publication_date, source_url patient_logs id, user_id, log_type, content, voice_url, sent_to_doctor, created_at

• Run Tests

cd frontend

• npm test

cd backend

• pytest

• cd ai-services
• pytest

Frontend (Vercel)

• cd frontend
• vercel deploy --prod Backend (Railway/Render)
• cd backend

Push to GitHub Connect repo to hosting platform. Auto-deploy on push

• Frontend: https://doc-app.vercel.app
• Backend API: https://doc-api.railway.app
• Documentation: https://doc-api.railway.app/docs

Frontend Developer - React UI/UX Implementation

Backend Developer - FastAPI + Database Architecture

AI Developer - ML Models + NLP + OCR Services

MIT License - See LICENSE file

OpenFDA for drug data Anthropic for Claude API Beers Criteria for geriatric medication guidelines

📞 Support For issues: GitHub Issues For questions: [email protected] Built for safer medication management