This project is a backend system for a Clinical AI Assistant application that helps healthcare professionals with patient data management, clinical decision support, and medical documentation. The system processes medical data, provides AI-powered insights, and maintains secure access to patient information.

• User Authentication: Secure login system for healthcare professionals
• Patient Data Management: Store and retrieve patient medical records
• Clinical Decision Support: AI-powered analysis of patient data to suggest diagnoses and treatments
• Medical Documentation: Automated generation of clinical notes and reports
• Secure API Integration: Connect with external medical systems and databases

• Node.js: Server-side JavaScript runtime
• Express.js: Web framework for building RESTful APIs
• MongoDB: NoSQL database for storing medical data
• JWT Authentication: Secure access control for healthcare professionals
• AI Integration: Connection to clinical decision support models

• POST /api/auth/register - Register new healthcare professional
• POST /api/auth/login - Authenticate and receive access token
• POST /api/auth/refresh - Refresh authentication token

• GET /api/patients - List patients under provider's care
• GET /api/patients/:id - View specific patient details
• POST /api/patients - Add new patient record
• PUT /api/patients/:id - Update patient information

• GET /api/clinical-data/:patientId - Retrieve patient clinical data
• POST /api/clinical-data/:patientId - Add new clinical observations
• PUT /api/clinical-data/:id - Update existing clinical data

• POST /api/ai/diagnose - Get AI-powered diagnostic suggestions
• POST /api/ai/treatment - Receive treatment recommendations
• POST /api/ai/document - Generate clinical documentation
• POST /api/ai/literature - Search relevant medical literature

• Encrypted patient data storage
• Role-based access control for different healthcare providers
• Audit trails for all data access and modifications
• Compliance with healthcare data regulations

# Install dependencies
npm install

# Development mode with hot reloading
npm run dev

# Production mode
npm start

The application is deployed on Replit, with automatic scaling to handle varying loads of clinical requests.

This project is currently in development, with ongoing improvements to AI capabilities and integration with additional medical information systems.