Faysal-MD/An-Interpretable-Deep-Learning-Approach-for-Skin-Cancer-Categorization-IEEE2023
Multiclass skin cancer detection using explainable AI for checking the models' robustness
This project offers an interpretable deep learning method to classify different types of skin cancer from images. It takes dermoscopic images of skin lesions as input and outputs a categorization of the lesion, along with explanations for the classification. Dermatologists and medical researchers would find this valuable for supporting diagnostic processes and understanding AI decisions.
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Use this if you are a dermatologist or medical researcher interested in an AI tool that not only classifies skin lesions but also provides insight into its decision-making process.
Not ideal if you need a fully validated, production-ready diagnostic tool for direct patient care, as this is a research project.
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MIT
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May 27, 2024
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