Skin cancer classification using deep learning
Abstract
Skin cancer is a disease that affects people with dark or light skin tone. On the other hand, more and more people tend to use tanning beds or spend prolonged periods of time in the sun's rays, causing this disease to be more frequent. As a complement in the diagnosis of this disease there is artificial intelligence, which allows the use of classification algorithms such as decision trees, vector support machines, logistic regression, among others; In addition, the use of deep learning algorithms such as convolutional neural networks, helping to make a pre-diagnosis of skin cancer. This article will explain the development of a method, in which, using the database of dermatological images published by the International Skin Imaging Collaboration (ISIC) \citep{ISIC:12}, a set of images is considered which have already been been characterized by specialists and found in a group of benign and malignant.
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