charanhu/Skin_Cancer_Detection_MNIST
The dataset consists of 10015 dermatoscopic images which can serve as a training set for academic machine learning purposes. The objective to build deep learning model to classify given query image into one of the 7 different classes of skin cancer.
This project offers a tool for classifying dermatoscopic images to help with preliminary skin cancer detection. You input a dermatoscopic image, and the system outputs a classification into one of seven types of skin cancer. This tool is designed for dermatologists or medical researchers who need an initial assessment or a research aid for identifying skin conditions.
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Use this if you are a dermatologist or medical researcher needing to quickly classify dermatoscopic images for potential skin cancer types.
Not ideal if you need a diagnostic tool for clinical use, as this is a research model and not medically certified.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Aug 17, 2022
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