Melanoma Skin Cancer Detection with the Integration of a Conversational Chatbot
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Abstract
Skin cancer, specifically melanoma, results from abnormal melanocytic cell growth and can be fatal. It typically appears as dark lesions due to UV exposure and genetic factors. Early detection is crucial fortreatment. The conventional method, biopsy, is invasive, painful, and slow, as it requires lab analysis. To address these issues, a non- invasive computer-aided diagnosis (CAD) system is proposed, using dermoscopy images. This system preprocesses the images, segments the lesion, extracts unique features, and then classifies the skin as normal or cancerous using a support vector machine (SVM). The SVM with a linear kernel demonstrates optimal accuracy. CAD eliminates the need for physical contact, reducing pain and improving efficiency in melanoma detection through advanced image processing techniques.
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