A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi

Background Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists’ experience and fails to achieve adequate accuracy and reproducibility in discriminating atypical nevi (AN) from early melanomas (EM). Objective We aimed to develop a Deep Convolutional Neural Network (DCNN) model able to support...