Ai-Symptom-analysis

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Ai-Symptom-analysis

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AI Symptom Analyzer is an AI-powered healthcare application that helps users understand potential health conditions based on the symptoms they provide. By utilizing advanced AI models, the platform analyzes user inputs and generates possible insights, precautionary measures, and health recommendations in a simple and user-friendly interface. Built

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# MediRoute AI — Full-Stack AI Healthcare Triage

MediRoute AI is a production-ready web application designed for intelligent symptom triage and clinical routing. Built with a premium "Glassmorphism" aesthetic, it combines real-time AI analysis with map-based hospital routing.

## 🚀 Features
- **🧠 AI Symptom Analyzer**: Natural language processing to determine urgency (Claude API).
- **🎤 Voice Input**: Hands-free symptom description with live waveform visualization.
- **🗺️ Smart Doctor Routing**: Automatically routes to the correct specialist at nearby clinics.
- **📊 Health Dashboard**: Tracks symptom history and risk trends using Recharts.
- **🚨 Emergency Mode**: High-priority UI triggers for life-threatening symptoms.
- **🌐 Multilingual Support**: English and Hindi support for broader accessibility.

## 🛠️ Tech Stack
- **Frontend**: Next.js 14, Tailwind CSS, Framer Motion, Lucide React, Recharts.
- **Backend**: Node.js, Express, @anthropic-ai/sdk.
- **Database**: Supabase (PostgreSQL) with mock fallbacks for instant testing.
- **AI**: Claude 3 (Anthropic) for clinical triage logic.

## 📦 Installation & Setup

### 1. Backend Setup
```bash
cd backend
npm install
cp .env.example .env
# Add your ANTHROPIC_API_KEY to .env
npm run dev # or node index.js
```

### 2. Frontend Setup
```bash
cd frontend
npm install
cp .env.local.example .env.local
# Add your config to .env.local
npm run dev
```

## 🚀 Deployment to Render

You can easily deploy MediRoute AI to Render using Render Blueprints. The project includes a pre-configured `render.yaml` that sets up both the Express backend and the Next.js frontend automatically.

[![Deploy to Render](https://render.com/images/deploy-to-render-button.svg)](https://render.com/deploy)

### Step-by-Step Instructions:
1. **Push to GitHub**: Push your local repository to a private or public GitHub repository.
2. **Deploy via Render**:
   - Go to the [Render Dashboard](https://dashboard.render.com).
   - Click **New** (top right) and select **Blueprint**.
   - Connect your GitHub repository.
   - Render will read the `render.yaml` and prompt you to enter the environment variables.
3. **Environment Variables**:
   - **`GROQ_API_KEY`**: Your Groq API key for clinical triage (Required).
   - **`NEXT_PUBLIC_BACKEND_URL`**: The public URL of your backend. By default, it is configured to reference `https://mediroute-api.onrender.com/api`. If you customize the backend service name, update this URL accordingly.
   - **`SUPABASE_URL` & `SUPABASE_ANON_KEY`** (Optional): Supabase credentials. If not set, the application will fallback to high-fidelity mock data.
   - **`GEMINI_API_KEY`** (Optional): Gemini API key for visual symptom analysis.
   - **`FIREBASE_SERVICE_ACCOUNT`** (Optional): Firebase Admin SDK credentials in JSON format. If not set, user authentication claims will be processed in local verification fallback mode.

---

## 🧪 Testing the App
1. **Low Urgency**: "I have a slight headache and a scratchy throat."
2. **Medium Urgency**: "My stomach has been hurting sharply for two days."
3. **Emergency**: "I am experiencing severe chest pain and left arm numbness."

---
Built with ❤️ for the Future of Healthcare.

Ai-Symptom-analysis

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