Deep Learning–Based Methods for Automatic Diagnosis of Skin Lesions

The main purpose of the study was to develop a high accuracy system able to diagnose skin lesions using deep learning–based methods. We propose a new decision system based on multiple classifiers like neural networks and feature–based methods. Each classifier (method) gives the final decision system a certain weight, depending on the calculated accuracy, helping the system make a better decision. First, we created a neural network (NN) that can differentiate melanoma from benign nevus. The NN architecture is analyzed by evaluating it during the training process.