RadCare Assistant is a tool that helps analyze chest X-ray images using machine learning. It can detect various conditions from X-ray images and provide quick analysis to support healthcare professionals.
- Upload and analyze chest X-ray images
- Automated detection of common chest conditions
- User-friendly interface for medical professionals
- Secure storage of analysis results
RadCare Assistant was inspired by and trained on the NIH Chest X-ray Dataset, a large publicly available dataset of chest X-ray images provided by the National Institutes of Health. This dataset consists of over 100,000 anonymized chest X-ray images with corresponding medical annotations, making it an invaluable resource for developing machine learning models for medical image analysis.
- Make sure you have Docker installed on your computer
- Clone this repository
- Build the Docker image:
docker build -t radcare_assistant . - Run the container:
docker run -p 8000:8000 radcare_assistant
- Open the application in your web browser at http://localhost:8000
- Upload a chest X-ray image
- Wait for the analysis to complete
- View the results and recommendations
- Docker
- Internet connection for initial setup
