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Results are not a substitute for professional medical advice.
A high-resolution image capturing the entirety of the affected skin region is uploaded and then transmitted to the backend for further processing.
View MoreThe image is subsequently processed to ensure compatibility with the MobileNet V2 model.
View MoreThen the image is fed into the model, which then predicts top three most likely skin conditions from a list that includes actinic keratosis (AK), basal cell carcinoma (BCC), benign keratosis (BK), dermatofibroma (DF), melanocytic nevi (NV), melanoma (MEL), and vascular skin lesions (VASC).
View MoreAfter the MobileNet V2 model generates predictions, they are transmitted from the backend and presented to the end user on the frontend.
View MoreThis project leverages Python, Keras, TensorFlow, scikit-learn, HTML5, CSS, JS, and Bootstrap, hosted on GitHub, to create a dynamic and interactive website.
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