This machine learning model is designed to predict whether a foot is affected by gangrene and to identify the specific type of gangrene: dry, wet, or gas, or to determine if the foot is normal.
Gangrene is a serious medical condition that occurs when body tissue dies due to lack of blood flow or a severe bacterial infection. It typically affects the extremities, such as the feet and hands. Early detection and treatment are crucial for preventing severe complications. Our model aims to assist medical professionals and individuals in identifying the presence and type of ga8ngrene using advanced machine learning techniques.
- Prediction of Gangrene Presence: Determines whether the foot has gangrene or is normal.
- Classification of Gangrene Types: Identifies the type of gangrene (dry, wet, gas) if present.
- User-friendly Web Interface: Easy-to-use interface for uploading foot images and viewing predictions.
Here are examples of predictions made by our model for all four categories:
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Normal Foot: Normal Foot Prediction
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Dry Gangrene: Dry Gangrene Prediction
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Wet Gangrene: Wet Gangrene Prediction
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Gas Gangrene: Gas Gangrene Prediction
This project is ongoing, and we are constantly working to improve the accuracy and reliability of our model. We are actively seeking datasets to enhance our training process. If you have relevant datasets or are interested in collaborating with us, please contact us.
We are exploring the integration of Web3 technologies to enhance data security and privacy, ensuring that user data is handled with the utmost care and confidentiality.
We welcome contributions. Whether you have expertise in machine learning, medical imaging, or Web3 technologies, your input can be invaluable to our project.
If you have datasets, suggestions, or any questions, please reach out to us at Mail.
Thank you for your interest and support!