A pretrained neural network shows similar diagnostic accuracy to medical students in categorizing dermatoscopic images after comparable training conditions

Automated image classification by machine vision is evolving, largely because of the increasing efficiency of neural networks with special architectures such as convolutional neural networks (CNN)(1) . A recent study comparing board certified dermatologists with CNN suggested that CNN may achieve diagnostic accuracies similar to human experts(2) . We demonstrated that medical students without prior knowledge of dermatoscopy learn equally well from an analytic or heuristic teaching approach(3) . This article is protected by copyright. All rights reserved.