README.md

metadata

title: MedGemma Symptom Analyzer
emoji: 🏥
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: apache-2.0

MedGemma Symptom Analyzer 🏥

An AI-powered symptom analysis tool built with Google's MedGemma model and Gradio. This application provides preliminary medical insights based on symptom descriptions.

Features

• Symptom Analysis: Enter symptoms and get AI-powered medical insights
• Differential Diagnosis: Possible conditions based on presented symptoms
• Medical Recommendations: Next steps and when to seek immediate care
• Interactive Interface: User-friendly Gradio web interface
• Example Symptoms: Pre-built examples to try the system

How to Use

1. Enter Symptoms: Describe your symptoms in the text area
2. Adjust Settings: Use the temperature slider to control response creativity
3. Analyze: Click "Analyze Symptoms" to get medical insights
4. Review Results: Read the AI-generated analysis and recommendations

Important Disclaimers

⚠️ This tool is for educational purposes only and should not replace professional medical advice.

• Always consult with healthcare professionals for medical concerns
• Seek immediate medical attention for severe or emergency symptoms
• The AI may not always provide accurate medical information
• This is not a substitute for proper medical diagnosis

Model Information

This application uses Google's MedGemma-2B model, specifically fine-tuned for medical applications. The model is optimized with:

• 4-bit quantization for efficient inference
• Automatic device mapping for optimal performance
• Temperature-controlled generation for balanced responses

Technical Details

• Framework: Gradio for the web interface
• Model: google/medgemma-2b via Hugging Face Transformers
• Optimization: BitsAndBytesConfig for memory efficiency
• Hardware: GPU-accelerated inference when available

Local Development

To run this locally:

pip install -r requirements.txt
python app.py

License

This project is licensed under the Apache License 2.0.

Acknowledgments

• Google for the MedGemma model
• Hugging Face for the Transformers library
• Gradio team for the interface framework