Harnessing Deep Learning for Accurate Multi-Class Classification of Skin Cancer Types
DOI:
https://doi.org/10.48047/Keywords:
Skin cancer, Multi-class classification, CNN.Abstract
The skin, being the largest organ in the human body, plays a vital role in protecting muscles, bones, and other tissues. When skin functionality is compromised, it can adversely affect overall health. Due to its sensitivity, the skin is particularly vulnerable to environmental factors such as sunlight and pollution, which can lead to skin cancer. Skin cancer primarily manifests in two forms: benign and melanoma. While benign lesions, like moles, remain superficial and non-invasive, melanoma poses a serious threat,
often resulting in sores and bleeding. It originates from melanocytes and is considered more hazardous. In the United States, over 700,000 skin lesions are diagnosed annually, as reported by the American Cancer Society.
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References
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N. Hameed, A. M. Shabut and M. A. Hossain, "Multi-Class Skin Diseases Classification Using Deep Convolutional Neural Network and Support Vector Machine," 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), 2018, pp. 1-7, doi: 10.1109/SKIMA.2018.8631525.
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