Skin Cancer Cell Detection Using Machine Learning and Image Processing
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Abstract
Skin Cancer in today’s scenario is the most trending and common of all the cancers that directly affect the skin of the patient. It is the fifth most common type of cancer found in men and the sixth most common type in women. Surgery, Chemotherapy, Radiation therapy, and immunotherapy techniques are used to kill cancer cells. The research investigated cancer detection, thoroughly discussed it, and proposed the methodologies for early diagnosis of the diseases using image processing and machine learning. The proposed model is designed with the procedures of collection of dermoscopy images and undergoes pre-processing, segmentation, feature selection, and predictions. Multiple algorithms were utilized for the medical diagnosis of the cancer cells including Conventional neural network (CNN), Support vector machine (SVM), Decision Tree, and Random Forest to detect the cancer cells with higher accuracy.
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