🚀 ArogyaAI — AI-Powered Healthcare Analysis Platform

🩺 Smart Health Insights | 🤖 AI Triage | 📄 Intelligent Reports
Built to make healthcare guidance fast, accessible, and scalable

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🧠 Overview

ArogyaAI is a full-stack MERN application that leverages Google Gemini AI to analyze symptoms, prescriptions, and health data.

It delivers structured medical insights, triage detection, and actionable recommendations — helping users make faster and smarter healthcare decisions.

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✨ Key Features

• 🧠 AI Symptom Analysis
• 🚨 Emergency Triage Detection
• 🖼️ Prescription & Image Analysis
• 📄 PDF Medical Reports
• 🔐 JWT Authentication System
• 📊 Analysis History Tracking
• 🛡️ Enterprise-Level Security

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🏗️ Tech Stack

Layer	Technology
Frontend	React, Tailwind CSS, Vite
Backend	Node.js, Express
Database	MongoDB, Mongoose
AI Engine	Google Gemini API
Auth	JWT
Security	Helmet, Rate Limiting, Joi

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📸 Demo Preview

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⚙️ Quick Start

1️⃣ Clone Repository

git clone https://github.com/Xenon010101/ArogyaAI.git
cd ArogyaAI

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2️⃣ Setup Environment

cp backend/.env.example backend/.env
cp frontend/.env.example frontend/.env

Edit backend/.env:

PORT=5000
NODE_ENV=development
MONGODB_URI=your_mongodb_uri
JWT_SECRET=your_secure_secret
JWT_EXPIRES_IN=7d
GEMINI_API_KEY=your_gemini_api_key
CLIENT_URL=http://localhost:5173

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3️⃣ Install Dependencies

# Backend
cd backend && npm install

# Frontend
cd ../frontend && npm install

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4️⃣ Run Development

# Backend
cd backend
npm run dev

# Frontend
cd frontend
npm run dev

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🌐 Access

• Frontend → http://localhost:5173
• Backend → http://localhost:5000

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🚀 Production Deployment

cd frontend
npm run build

Environment Variables

Backend

• NODE_ENV=production
• MONGODB_URI
• JWT_SECRET
• GEMINI_API_KEY
• CLIENT_URL

Frontend

• VITE_API_URL

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📡 API Overview

🔐 Authentication

• POST /api/auth/register
• POST /api/auth/login
• GET /api/auth/me
• PATCH /api/auth/reset-password/:token

🧠 Analysis

• POST /api/analyze
• GET /api/analyze/:id
• GET /api/analyze/my-analyses
• POST /api/analyze/pre-check

❤️ Health

• GET /api/health

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🧠 AI Response Structure

{
  "risk_level": "low | moderate | high | critical",
  "summary": "Brief analysis",
  "conditions": ["Possible conditions"],
  "recommendations": ["Next steps"],
  "red_flags": ["Warning signs"],
  "confidence": 0.0
}

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📁 Project Structure

ArogyaAI/
├── backend/
│   ├── src/
│   ├── config/
│   ├── controllers/
│   ├── models/
│   ├── routes/
│   ├── services/
│   └── utils/
├── frontend/
│   ├── src/
│   ├── components/
│   ├── pages/
│   └── hooks/

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🔒 Security

• 🔐 JWT Authentication
• 🛡️ Helmet Security Headers
• 🚦 Rate Limiting
• 🧼 Input Validation (Joi)
• ❌ XSS Protection
• 🌐 CORS Configuration
• 🔑 Bcrypt Password Hashing

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🌍 Real-World Impact

• 🏥 Faster preliminary diagnosis
• 🌍 Helps rural & low-access areas
• ⏳ Reduces unnecessary hospital visits
• 📊 Supports doctors with structured insights

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🏆 Hackathon Highlights

• 💡 Real-world problem solving
• 🤖 AI + Full Stack integration
• 📈 Scalable architecture
• 🌍 Social impact driven

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🔮 Future Improvements

• 📱 Mobile App (Flutter)
• 🌐 Multi-language support
• 🧠 Fine-tuned AI model
• 📊 Health analytics dashboard
• 🏥 Doctor-patient integration

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🤝 Contributing

git checkout -b feature-name
git commit -m "Add feature"
git push origin feature-name

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👨‍💻 Author

Anmol Patel 🔗 https://github.com/Xenon010101

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🤝 Contributors

• Akshita 🔗 https://github.com/Akshita-2307

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⭐ Support

If you like this project:

• Star ⭐ the repo
• Share it on LinkedIn

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💬 Feedback

Have suggestions or ideas? Feel free to open an issue or connect! 🚀