🩺 MedicalGPT

A powerful clinical decision support system that leverages RAG (Retrieval Augmented Generation) to provide diagnostic insights based on patient cases.

🌟 Features

• Clinical Query Interface: Simple and intuitive interface for entering medical queries
• Case Retrieval: Efficiently retrieves relevant patient cases using FAISS similarity search
• AI-Powered Analysis: Generates diagnostic insights using state-of-the-art language models
• Modern UI: Clean, responsive interface built with Streamlit
• Context Display: Expandable view of retrieved clinical notes for transparency

🚀 Getting Started

Prerequisites

• Python 3.7+
• pip package manager

Installation

1. Clone the repository:

git clone https://github.com/yourusername/MedicalGPT.git
cd MedicalGPT

2. Install dependencies:

pip install -r requirements.txt

Running the Application

Launch the application using Streamlit:

streamlit run app.py

The application will be available at http://localhost:8501 by default.

📦 Project Structure

MedicalGPT/
├── app.py              # Main Streamlit application
├── assets/            # Static assets
├── data/             # Clinical data and embeddings
├── src/              # Source code
│   ├── retriever.py  # Document retrieval logic
│   └── generator.py  # Text generation components
└── requirements.txt   # Project dependencies

🛠️ Technologies Used

• Streamlit: Web interface and application framework
• FAISS: Efficient similarity search and clustering
• Sentence Transformers: Text embeddings for retrieval
• PyTorch: Deep learning framework
• Transformers: NLP models for text generation
• Pandas: Data manipulation and analysis

💡 Usage

1. Enter a clinical query in the text input field
2. The system will retrieve relevant patient cases
3. Review the retrieved clinical notes in the expandable sections
4. Examine the AI-generated diagnostic insights

📝 Note

This tool is designed to assist medical professionals and should not be used as a replacement for professional medical judgment. Always consult with qualified healthcare providers for medical decisions.