A comprehensive AI-powered healthcare information system that helps users identify diseases, get medicine recommendations, and find nearby healthcare facilities.

• AI-Powered Diagnosis: Advanced symptom analysis using machine learning algorithms
• Medicine Recommendations: Over-the-counter medicine suggestions with pricing
• Clinic Finder: Government-approved healthcare facilities with real-time availability
• Patient Profiles: Secure patient data management and medical history tracking
• Admin Dashboard: Comprehensive system management and analytics

• Self-Learning System: Continuous improvement based on user feedback
• Pattern Recognition: Identifies disease trends and seasonal patterns
• Accuracy Tracking: Monitors diagnostic accuracy and user satisfaction
• Predictive Analytics: Forecasts health trends and system usage

• Data Encryption: Secure storage of medical information
• HIPAA Compliance: Healthcare data protection standards
• Privacy Controls: User data control and consent management
• Audit Trails: Complete system activity logging

• Frontend: React 18 + TypeScript + Tailwind CSS
• Icons: Lucide React
• Build Tool: Vite
• Styling: Tailwind CSS with custom design system
• State Management: React Hooks + Local Storage
• Testing: Vitest
• Type Safety: TypeScript with strict mode

src/
├── components/           # React components
│   ├── Header.tsx       # Navigation header
│   ├── HomePage.tsx     # Landing page
│   ├── DiagnosisPage.tsx # Symptom analysis
│   ├── ClinicsPage.tsx  # Healthcare facility finder
│   ├── ProfilePage.tsx  # Patient management
│   └── AdminPage.tsx    # System administration
├── data/                # Static data
│   ├── diseases.ts      # Disease database
│   ├── medicines.ts     # Medicine catalog
│   ├── clinics.ts       # Healthcare facilities
│   └── questions.ts     # Diagnostic questions
├── hooks/               # Custom React hooks
│   └── useLocalStorage.ts
├── types/               # TypeScript definitions
│   └── index.ts
├── utils/               # Utility functions
│   ├── diagnosisEngine.ts # AI diagnosis logic
│   └── aiLearning.ts    # Machine learning system
└── App.tsx             # Main application

• Node.js 18+
• npm or yarn

1. Clone the repository

git clone <repository-url>
cd healthcare-advisor-system

2. Install dependencies

npm install

3. Start development server

npm run dev

4. Build for production

npm run build

# Initialize git repository
git init

# Add all files
git add .

# Commit changes
git commit -m "Initial commit: Healthcare Advisor System"

# Add remote repository
git remote add origin <remote-repository-url>

# Push to remote
git push -u origin main

# Pull latest changes
git pull origin main

1. Create Dockerfile

FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build
EXPOSE 3000
CMD ["npm", "run", "preview"]

2. Build Docker image

docker build -t healthcare-advisor .

3. Run Docker container

docker run -p 3000:3000 healthcare-advisor

4. Docker Compose for multiple containers

version: '3.8'
services:
  frontend:
    build: .
    ports:
      - "3000:3000"
  nginx:
    image: nginx:alpine
    ports:
      - "80:80"
    volumes:
      - ./nginx.conf:/etc/nginx/nginx.conf

Create Jenkinsfile:

pipeline {
    agent any
    
    stages {
        stage('Checkout') {
            steps {
                git 'https://github.com/your-repo/healthcare-advisor.git'
            }
        }
        
        stage('Install Dependencies') {
            steps {
                sh 'npm install'
            }
        }
        
        stage('Build') {
            steps {
                sh 'npm run build'
            }
        }
        
        stage('Test') {
            steps {
                sh 'npm run test'
            }
        }
        
        stage('Docker Build') {
            steps {
                sh 'docker build -t healthcare-advisor:${BUILD_NUMBER} .'
            }
        }
        
        stage('Deploy') {
            steps {
                sh 'docker run -d -p 3000:3000 healthcare-advisor:${BUILD_NUMBER}'
            }
        }
    }
}

1. Create EC2 Instance

   • Launch Ubuntu 20.04 LTS instance
   • Configure security groups (ports 22, 80, 443, 3000)
   • Create and download key pair

2. Connect to EC2

ssh -i your-key.pem ubuntu@your-ec2-ip

3. Setup Environment

# Update system
sudo apt update && sudo apt upgrade -y

# Install Node.js
curl -fsSL https://deb.nodesource.com/setup_18.x | sudo -E bash -
sudo apt-get install -y nodejs

# Install Docker
sudo apt-get install docker.io -y
sudo systemctl start docker
sudo systemctl enable docker

# Install Jenkins
wget -q -O - https://pkg.jenkins.io/debian/jenkins.io.key | sudo apt-key add -
sudo sh -c 'echo deb http://pkg.jenkins.io/debian-stable binary/ > /etc/apt/sources.list.d/jenkins.list'
sudo apt-get update
sudo apt-get install jenkins -y

4. Deploy Application

# Clone repository
git clone <your-repo-url>
cd healthcare-advisor-system

# Install dependencies and build
npm install
npm run build

# Start application with PM2
sudo npm install -g pm2
pm2 start npm --name "healthcare-advisor" -- run preview
pm2 startup
pm2 save

• Diagnostic Accuracy: Tracks AI prediction accuracy
• User Satisfaction: Monitors feedback and ratings
• System Performance: Response times and availability
• Usage Analytics: Patient interactions and popular features

• Lazy Loading: Components loaded on demand
• Code Splitting: Optimized bundle sizes
• Caching Strategy: Local storage for offline capability
• CDN Integration: Fast asset delivery

• Encryption: AES-256 encryption for sensitive data
• Authentication: Secure user authentication system
• Access Control: Role-based permissions
• Data Anonymization: Privacy-first approach

• HIPAA Compliance: Healthcare data protection
• GDPR Ready: European data protection standards
• Audit Logging: Complete activity tracking
• Security Headers: XSS and CSRF protection

• Total patients registered
• Daily/monthly consultation trends
• Most common symptoms and diseases
• Medicine recommendation accuracy
• Clinic utilization rates
• User satisfaction scores

• Diagnostic pattern recognition
• Seasonal disease trends
• Treatment effectiveness tracking
• System improvement recommendations

• Telemedicine Integration: Video consultations
• IoT Device Support: Wearable device data integration
• Multi-language Support: Localization for global use
• Mobile Application: Native iOS/Android apps
• Advanced AI Models: Deep learning for better accuracy

• Microservices Architecture: Service decomposition
• Cloud Migration: AWS/Azure cloud deployment
• Load Balancing: High availability setup
• Database Optimization: Performance improvements

• Issue Tracking: GitHub Issues for bug reports
• Documentation: Comprehensive API documentation
• Community: Developer community support
• Professional Support: Enterprise support options

1. Fork the repository
2. Create feature branch (git checkout -b feature/AmazingFeature)
3. Commit changes (git commit -m 'Add AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open Pull Request

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

This system is for informational purposes only and should not replace professional medical advice. Always consult healthcare professionals for medical decisions.

Healthcare Advisor System - Empowering healthcare through AI technology