Melanoma Skin Cancer Detection Using Recent Deep Learning Models

Abstract

Melanoma is considered as one of the world's deadly cancers. This type of skin cancer will spread to other areas of the body if not detected at an early stage. Convolutional Neural Network (CNN) based classifiers are currently considered one of the most effective melanoma detection techniques. This study presents the use of recent deep CNN approaches to detect melanoma skin cancer and investigate suspicious lesions. Tests were conducted using a set of more than 36,000 images extracted from multiple datasets. The obtained results show that the best performing deep learning approach achieves high scores with an accuracy and Area Under Curve (AUC) above 99%.

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