🩺 Medical Symptom Checker

An intelligent medical triage and disease prediction system powered by:

• ✅ Machine learning (Decision Tree)
• ✅ Rule-based reasoning
• ✅ Retrieval-Augmented Generation (RAG) using SerpAPI and GROQ
• ✅ Streamlit interactive web app

• 🌟 Symptom validation & risk assessment
• 🌟 Severity classification (LOW / MEDIUM / HIGH)
• 🌟 Care recommendations (e.g., SELF CARE, CONSULT DOCTOR)
• 🌟 Disease prediction (ML + rule-based fallback)
• 🌟 Precautions & condition info fetched live via SerpAPI (RAG)
• 🌟 User-friendly Streamlit app for real-time triage

Medical-Symptom-Checker/
├── data/                  # Medical datasets (symptoms, severity, etc.)
├── symptom_checker/        # Core logic modules (triage, ML, RAG, etc.)
├── app.py                  # Streamlit frontend
├── main.py                 # CLI runner
├── requirements.txt        # Python dependencies
└── README.md               # This file

git clone https://github.com/aks3003/Medical-Symptom-Checker.git
cd Medical-Symptom-Checker

pip install -r requirements.txt

Create a .env or safe.env file with your SERPAPI key:

SERP=your_serpapi_key
GROQ=your_GROQ_key

streamlit run app.py

python main.py

📋 Triage Summary
✅ Validated Symptoms: ['fever', 'cough']
💥 Risk Score: 10
⚠️ Severity Level: MEDIUM
💡 Care Recommendation: CONSULT DOCTOR

🩺 Predicted Diseases and Details:
➡ Disease: pneumonia
   Description: Pneumonia is an infection of the lungs...
   Precautions: Get vaccinated, wash hands, avoid smoking...

• This tool is for educational/demo purposes only and not a replacement for professional medical advice.
• API keys (e.g., SerpAPI) should be kept secure in .env.

• Add support for other ML models (e.g., XGBoost)
• Use GROQ API for richer RAG summarization
• Dockerize for easy deployment

Built with ❤️ by aks3003