CXRTNet is a chest X-ray and CT scan pathology classification tool that utilizes deep learning techniques to analyze medical images and provide probabilities of various diseases present in the images. This project aims to streamline the process of diagnosing chest-related conditions by providing healthcare professionals with rapid and accurate insights derived from medical imaging data.

• Upload chest X-ray and CT scan images for analysis.
• Receive instant probability estimates for diseases such as pneumonia, lung cancer, tuberculosis, and more.
• User-friendly interface for easy interaction.
• Fast processing times for quick results.

1. Clone the repository:

   git clone https://github.com/syedhaashir/Alligator.git
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Run the application:

   python app.py
   

4. Access the application through your web browser at http:https://localhost:5000.

1. Upload your chest X-ray or CT scan image.
2. Wait for the analysis to complete.
3. View the probability estimates for various diseases.
4. Interpret the results and take necessary actions based on the findings.

Contributions are welcome! If you'd like to contribute to CXRTNet, please fork the repository and create a new pull request. Additionally, feel free to open an issue for any bug fixes, feature requests, or general feedback.

CXRTNet was inspired by the need for efficient and accurate tools in medical imaging analysis. We would like to thank the open-source community for their invaluable contributions to the field of deep learning and healthcare technology.