https://github.com/mindscope-world/ai-medical-imaging
https://github.com/mindscope-world/ai-medical-imaging
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/mindscope-world/ai-medical-imaging
- Owner: mindscope-world
- License: mit
- Created: 2024-12-27T08:00:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-31T15:13:55.000Z (over 1 year ago)
- Last Synced: 2025-03-09T07:18:10.370Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 1.88 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🏥 Medical Imaging Diagnosis Agent
## Overview
This project is a **Medical Imaging Diagnosis Agent** that leverages **AI-powered analysis** to provide insights into medical imaging data. Built with Streamlit, it integrates advanced models like Google Gemini and DuckDuckGo search tools to assist healthcare professionals in diagnostics and research.
## Key Features
- **AI-Powered Analysis**: Utilizes the Google Gemini model for medical imaging diagnostics.
- **Streamlit UI**: Interactive and user-friendly interface for uploading and analyzing images.
- **Real-Time Research**: Integrates DuckDuckGo for on-the-fly research and references.
- **Educational Tool**: Designed for learning purposes with clear disclaimers for professional review.
## Installation
To run this application, follow these steps:
1. **Clone the repository:**
```bash
git clone
cd
```
2. **Install dependencies:**
```bash
pip install -r requirements.txt
```
3. **Set up your Google API Key:**
- Obtain your API key from [Google AI Studio](https://aistudio.google.com/apikey).
- Enter it in the Streamlit sidebar when prompted.
4. **Run the application:**
```bash
streamlit run app.py
```
## How to Use
1. **Launch the Application:**
- Open the provided link in your browser after running the Streamlit app.
2. **Configure the API Key:**
- Enter your Google API key in the sidebar to enable AI functionalities.
3. **Upload Medical Images:**
- Upload images in JPG, JPEG, PNG, or DICOM formats.
4. **Analyze Images:**
- Click on "Analyze Image" to receive detailed diagnostics and research insights.
5. **Review Results:**
- Examine the generated analysis, which includes diagnostic observations and patient-friendly explanations.
## Project Components
- **Streamlit**: Provides the frontend interface.
- **Google Gemini API**: Performs the AI-driven medical image analysis.
- **DuckDuckGo API**: Searches for supporting literature and references.
## Disclaimer
⚠️ **Important:** This tool is for educational and informational purposes only. It should not replace professional medical advice or diagnostics. Always consult qualified healthcare professionals for medical decisions.
## Contribution
Contributions are welcome! If you'd like to improve or extend the functionality of this project:
1. Fork the repository.
2. Create a new branch.
3. Commit your changes.
4. Submit a pull request.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contact
Feel free to reach out with any questions or suggestions:
- **Email:** [paulmwaura254@gmail.com]
- **LinkedIn:** [My LinkedIn Profile](https://www.linkedin.com/in/Paul-Ndirangu)
---
Happy coding! 🚀