MultiAgent-MedQA

This project implements a Multi-Agent Medical QA System designed to handle text-based medical queries and analyze X-ray images to provide accurate and detailed insights. The system consists of two specialized agents.

Overview

MultiAgent-MedQA is a cutting-edge system designed to address two crucial aspects of medical inquiry: processing text-based medical questions and analyzing X-ray images to provide accurate, detailed insights. This project leverages the power of multiple specialized agents to deliver robust responses to varied medical queries.

Architecture

Features

• Dual-Agent Architecture:

  • Text QA Agent: Handles natural language medical questions and provides evidence-based responses.
  • X-Ray Analysis Agent: Processes and analyzes X-ray images to assist in medical diagnosis and reinforce the text-based answers.

• Accurate Medical Insights:
  The system is built to deliver precise and detailed medical information by combining data-driven insights with expert heuristic models.

• Jupyter Notebook Based Implementation:
  The project is implemented entirely in Jupyter Notebook, making it easy to experiment with and iterate on models interactively.

Project Structure

Requirements

Before running the project, please ensure you have the following installed:

• Python 3.8 or above
• Jupyter Notebook or JupyterLab
• Essential Python libraries (e.g., numpy, pandas, scikit-learn, matplotlib, and any deep learning frameworks like TensorFlow or PyTorch as needed)

You can install these dependencies using:

pip install -r requirements.txt

Installation

1. Clone the repository:

   git clone https://github.com/VijayendraDwari/MultiAgent-MedQA.git

2. Change to the project directory:

   cd MultiAgent-MedQA

3. (Optional) Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate   # On Windows use `venv\Scripts\activate`

4. Install necessary dependencies:

   pip install -r requirements.txt

Usage

• Launching the Notebooks:
  Start the Jupyter Notebook server:

  jupyter notebook

  Open the notebooks in the notebooks/ directory to explore the implementation details of the Text QA and X-Ray Analysis agents.

• Interacting with the Agents:
  The notebooks provide interactive examples to:

  • Ask text-based medical queries and retrieve answers from the Text QA Agent.
  • Load and process X-ray images with the X-Ray Analysis Agent to assist in diagnosis.

Contributing

Contributions to MultiAgent-MedQA are highly welcome! To contribute:

1. Fork the repository.
2. Create a new branch with a descriptive name (e.g., feature/improve-xray-analysis).
3. Commit your changes with clear commit messages.
4. Open a pull request against the main branch detailing your changes and improvements.

Before starting, please consider reviewing our Contributing Guidelines for further details.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

Contact

For any questions or further inquiries, please reach out through:

• GitHub Issues: MultiAgent-MedQA Issues
• Email: [vijayendra.dwari@gmail.com]

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MultiAgent-MedQA strives to provide robust and reliable medical insights using innovative AI-driven approaches. Your feedback and contributions are valuable in enhancing the system further.