| | ---
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| | title: Digital Doctors Assistant ML API
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| | emoji: 🏥
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| | colorFrom: blue
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| | colorTo: purple
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| | sdk: docker
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| | pinned: false
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| | license: mit
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| | ---
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| |
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| | # Digital Doctors Assistant ML API
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| |
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| | A FastAPI-based machine learning service that provides two prediction models for healthcare applications:
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| |
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| | 1. **Risk Assessment Model** - Predicts patient risk levels (Low/Medium/High) based on vitals and health metrics
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| | 2. **Treatment Outcome Model** - Predicts treatment success probability based on patient data and medication
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| |
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| | ## Features
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| |
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| | - RESTful API endpoints for ML predictions
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| | - Interactive web interface for easy testing
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| | - ONNX Runtime for fast inference
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| | - Pre-trained models hosted on HuggingFace
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| | - Docker support for easy deployment
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| |
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| | ## Quick Start
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| |
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| | ### Using HuggingFace Space
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| |
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| | Simply visit the Space URL and use the web interface to make predictions.
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| |
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| | ### Run Locally with Docker
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| |
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| | ```bash
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| | docker run -it -p 7860:7860 \
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| | -e HUGGINGFACE_TOKEN="your_token_here" \
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| | registry.hf.space/your-username-your-space-name:latest
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| | ```
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| |
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| | ### Local Setup (Without Docker)
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| |
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| | 1. Install dependencies:
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| | ```bash
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| | pip install -r requirements.txt
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| | ```
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| |
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| | 2. Set your HuggingFace token:
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| | ```bash
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| | # Windows PowerShell
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| | $env:HUGGINGFACE_TOKEN="your_token_here"
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| |
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| | # Windows CMD
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| | set HUGGINGFACE_TOKEN=your_token_here
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| |
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| | # Linux/Mac
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| | export HUGGINGFACE_TOKEN=your_token_here
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| | ```
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| |
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| | 3. Run the server:
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| | ```bash
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| | uvicorn ml:app --host 0.0.0.0 --port 7860
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| | ```
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| |
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| | 4. Open your browser:
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| | - Web Interface: http://localhost:7860
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| | - API Docs: http://localhost:7860/docs
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| | - Health Check: http://localhost:7860/health
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| |
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| | ## API Endpoints
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| |
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| | ### POST /predict/risk
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| | Predict patient risk level based on health metrics.
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| |
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| | **Request Body:**
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| | ```json
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| | {
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| | "age": 45,
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| | "bmi": 28.5,
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| | "systolic_bp": 140,
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| | "diastolic_bp": 90,
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| | "chronic_conditions": "diabetes,hypertension",
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| | "severity_score": 7.5
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| | }
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| | ```
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| |
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| | **Response:**
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| | ```json
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| | {
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| | "success": true,
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| | "model": "risk_assessment",
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| | "prediction": "High",
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| | "confidence": 0.85,
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| | "probabilities": {
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| | "Low": 0.05,
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| | "Medium": 0.10,
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| | "High": 0.85
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| | }
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| | }
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| | ```
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| |
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| | ### POST /predict/treatment
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| | Predict treatment outcome success probability.
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| |
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| | **Request Body:**
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| | ```json
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| | {
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| | "patient_age": 55,
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| | "severity_score": 6.5,
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| | "compliance_rate": 0.85,
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| | "medication": "Metformin",
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| | "condition": "Diabetes Type 2"
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| | }
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| | ```
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| |
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| | **Response:**
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| | ```json
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| | {
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| | "success": true,
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| | "model": "treatment_outcome",
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| | "prediction": 1,
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| | "success_probability": 78.5,
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| | "confidence": 0.78,
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| | "probabilities": {
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| | "failure": 0.22,
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| | "success": 0.78
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| | }
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| | }
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| | ```
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| |
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| | ## Supported Medications
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| |
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| | - Paracetamol
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| | - Ibuprofen
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| | - Amoxicillin
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| | - Ciprofloxacin
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| | - Metformin
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| | - Lisinopril
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| | - Amlodipine
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| | - Omeprazole
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| |
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| | ## Supported Conditions
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| |
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| | - Common Cold
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| | - Influenza
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| | - Pneumonia
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| | - Bronchitis
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| | - Hypertension
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| | - Diabetes Type 2
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| | - Migraine
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| | - Gastroenteritis
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| |
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| | ## Environment Variables
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| |
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| | - `HUGGINGFACE_TOKEN` - Required. Your HuggingFace access token for downloading models
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| |
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| | ## Technology Stack
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| |
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| | - FastAPI - Web framework
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| | - ONNX Runtime - ML inference
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| | - NumPy - Numerical computing
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| | - HuggingFace Hub - Model hosting
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| | - Pydantic - Data validation
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| | - Uvicorn - ASGI server
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| |
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| | ## License
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| |
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| | MIT
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| |
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