ashioyajotham/Kenya-Clinical-Reasoning

# MedGemma Clinical Reasoning AI A Streamlit web application that uses Google's MedGemma-4B model to provide AI-powered clinical reasoning and decision support for Kenya healthcare professionals. ## 🚀 Quick Setup ### 1. Install Dependencies ```bash pip install -r requirements.txt ``` ### 2. Set Up Authentication 1. Get a Hugging Face token from huggingface.co 2. Copy `.env.example` to `.env`: ```bash copy .env.example .env ``` 3. Edit `.env` and replace `your_token_here` with your actual token: ``` HF_TOKEN=hf_your_actual_token_here ``` ### 3. Run the Application ```bash streamlit run streamlit_clinical_reasoning_app.py ``` ## 🏥 Features - **Real MedGemma AI**: Uses Google's MedGemma-4B model for medical reasoning - **Kenya Healthcare Context**: Optimized for Kenyan medical scenarios - **Demo Cases**: Pre-built clinical scenarios to try - **Interactive Interface**: Input your own clinical cases - **Clinical Settings**: Customize location, healthcare level, and specialty - **Download Reports**: Save clinical assessments as text files ## 📋 Demo Clinical Cases The app includes 5 pre-built demo cases: - Acute Abdominal Pain - Pediatric Fever and Cough - Hypertensive Crisis - Malaria Suspicion - Diabetic Emergency ## 🔧 System Requirements - **GPU**: 8GB+ VRAM recommended (for MedGemma-4B) - **RAM**: 16GB+ system memory - **Python**: 3.8+ - **CUDA**: Compatible GPU for best performance ## 🔒 Security - Environment variables are loaded from `.env` file - `.env` file is ignored by git to keep tokens secure - Use `.env.example` as a template ## ⚠️ Disclaimer This application is for educational and clinical decision support purposes only. Always consult qualified healthcare professionals for patient care decisions. ## 🇰🇪 Kenya Healthcare Integration The app is specifically designed for the Kenya healthcare system with: - All 47 Kenya counties - Kenya healthcare levels (1-6) - Local medical terminology - Regional health considerations