Resumen
The application of convolutional neural networks (CNN) has currently become a transversal tool for different areas. In the medical field several of the developed diagnosis aid systems are based on artificial intelligence. Particularly, there has been demonstrated its potential for detection and classification of different medical anomalies, such as skin cancer. Moreover, these intelligent systems have shown to be capable to recognize characteristics of skin cancer from images. This is a complex process due to the variability in the characteristics of the images and to the fact that there are different types of cancer. In this paper it is presented a review of different developed methods and systems, based on CNNs, for classification and detection of skin cancer, which were trained by using open access datasets.
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