Smart Healthcare Assistant

A comprehensive AI-powered healthcare platform that provides disease prediction, health monitoring, and intelligent chatbot assistance.

Project Structure

Backend (FastAPI + Python)

backend/
├── main.py                 # FastAPI application entry point
├── requirements.txt        # Python dependencies
├── .env.example           # Environment variables template
├── core/
│   ├── config.py          # Application configuration
│   ├── database.py        # MongoDB connection and setup
│   └── ml_models.py       # ML model management
├── models/                # Database models (Beanie/MongoDB)
│   ├── user.py            # User model
│   ├── health_record.py   # Health records model
│   ├── prediction.py      # Prediction results model
│   └── chat_history.py    # Chat conversation model
├── api/
│   └── routes/            # API route handlers
│       ├── auth.py        # Authentication endpoints
│       ├── users.py       # User management endpoints
│       ├── predictions.py # Disease prediction endpoints
│       ├── chat.py        # Chatbot endpoints
│       ├── dashboard.py   # Dashboard analytics endpoints
│       └── alerts.py      # Notification endpoints
└── models/                # ML model files (to be created)
    ├── heart_disease_model.joblib
    └── diabetes_model.joblib

Frontend (React + TypeScript)

frontend/
├── package.json           # Node.js dependencies
├── public/
│   ├── index.html         # Main HTML template
│   └── manifest.json      # PWA manifest
├── src/
│   ├── index.tsx          # Application entry point
│   ├── App.tsx            # Main App component
│   ├── index.css          # Global styles
│   ├── types/
│   │   └── index.ts       # TypeScript type definitions
│   ├── contexts/
│   │   └── AuthContext.tsx # Authentication context
│   ├── services/
│   │   └── api.ts         # API service layer
│   ├── components/
│   │   ├── common/        # Reusable components
│   │   │   └── LoadingSpinner.tsx
│   │   ├── layout/        # Layout components
│   │   │   └── Navbar.tsx
│   │   ├── forms/         # Form components
│   │   ├── charts/        # Chart components
│   │   └── prediction/    # Prediction-specific components
│   └── pages/             # Page components
│       ├── auth/          # Authentication pages
│       │   ├── LoginPage.tsx
│       │   └── RegisterPage.tsx
│       ├── dashboard/     # Dashboard page
│       │   └── DashboardPage.tsx
│       ├── predictions/   # Prediction pages
│       │   └── PredictionsPage.tsx
│       ├── chat/          # Chat page
│       │   └── ChatPage.tsx
│       ├── profile/       # Profile page
│       │   └── ProfilePage.tsx
│       └── health/        # Health records page
│           └── HealthRecordsPage.tsx

Key Features

🔬 AI-Powered Disease Prediction

• Heart Disease Prediction: ML model trained on cardiovascular risk factors
• Diabetes Risk Assessment: Predictive model for diabetes onset
• Risk Factor Analysis: Identifies key health risks and provides recommendations
• Multiple Model Support: Extensible architecture for additional disease models

💬 Intelligent Health Chatbot

• NLP-Powered Conversations: Uses transformer models for natural language understanding
• Health Q&A: Answers medical questions with contextual awareness
• Emergency Detection: Identifies urgent health situations requiring immediate attention
• Conversation History: Maintains chat history for better context

📊 Comprehensive Dashboard

• Health Analytics: Visual representation of health trends and predictions
• Risk Distribution: Charts showing risk levels across different health areas
• Prediction History: Timeline of all health assessments
• Personalized Insights: AI-generated health recommendations

🔔 Smart Alerts & Notifications

• Risk-Based Alerts: Automatic notifications for high-risk predictions
• Email & SMS Support: Multiple delivery channels for critical alerts
• Health Reminders: Scheduled notifications for health monitoring
• Emergency Contacts: Automatic notification of emergency contacts when needed

👤 User Management

• Secure Authentication: JWT-based authentication with role-based access
• Health Profiles: Comprehensive user health information management
• Medical History: Track allergies, medications, and past conditions
• Privacy Controls: User-controlled data sharing and privacy settings

Technology Stack

Backend (FARM Stack)

• FastAPI: Modern, fast web framework for building APIs
• MongoDB: NoSQL database for flexible health data storage
• Beanie: MongoDB ODM for Python with Pydantic integration
• Scikit-learn: Machine learning library for predictive models
• Transformers: Hugging Face library for NLP models
• PyTorch: Deep learning framework for advanced AI models

Frontend

• React 18: Modern React with hooks and concurrent features
• TypeScript: Type-safe JavaScript for better development experience
• Material-UI: Professional React component library
• React Query: Data fetching and caching library
• Recharts: Charting library for health data visualization
• React Router: Client-side routing for single-page application

Infrastructure & DevOps

• Docker: Containerization for easy deployment
• MongoDB Atlas: Cloud database service
• Vercel/Netlify: Frontend deployment platforms
• Heroku/DigitalOcean: Backend deployment options

Getting Started

Prerequisites

• Python 3.8+
• Node.js 16+
• MongoDB 4.4+
• Git

Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Create a virtual environment:

   python -m venv .venv

3. Activate the virtual environment:

   # On Windows (PowerShell/CMD):
   .venv\Scripts\activate
   
   # On Windows (Git Bash):
   source .venv/Scripts/activate
   
   # On macOS/Linux:
   source .venv/bin/activate

4. Upgrade pip (recommended):

   python -m pip install --upgrade pip

5. Install dependencies:

   pip install -r requirements.txt

6. Set up environment variables:

   # On Windows:
   copy .env.example .env
   
   # On macOS/Linux:
   cp .env.example .env
   
   # Edit .env with your configuration

7. Start the development server:

   uvicorn main:app --reload

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm start

Database Setup

1. Install MongoDB locally or use MongoDB Atlas
2. Create a database named healthcare_assistant
3. Update the MONGODB_URL in your .env file

API Documentation

The API documentation is automatically generated and available at:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

Development Guidelines

Code Style

• Backend: Follow PEP 8 guidelines for Python
• Frontend: Use ESLint and Prettier for code formatting
• TypeScript: Strict type checking enabled

Testing

• Backend: Use pytest for unit and integration tests
• Frontend: Use Jest and React Testing Library

Security Considerations

• JWT tokens for authentication
• Input validation and sanitization
• CORS configuration for cross-origin requests
• Environment variables for sensitive data
• Rate limiting for API endpoints

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Commit your changes: git commit -m 'Add feature'
4. Push to the branch: git push origin feature-name
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support and questions, please open an issue in the GitHub repository or contact the development team.

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Note: This is a comprehensive healthcare platform. Always consult with healthcare professionals for medical advice. This system is designed to supplement, not replace, professional medical consultation.