AK-DL: A Shallow Neural Network Model for Diagnosing Actinic Keratosis with Better Performance Than Deep Neural Networks.

ABSTRACT: Actinic keratosis (AK) is one of the most common precancerous skin lesions, which is easily confused with benign keratosis (BK). At present, the diagnosis of AK mainly depends on histopathological examination, and ignorance can easily occur in the early stage, thus missing the opportunity for treatment. In this study, we designed a shallow convolutional neural network (CNN) named actinic keratosis deep learning (AK-DL) and further developed an intelligent diagnostic system for AK based on the iOS platform. After data preprocessing, the AK-DL model was trained and tested with AK and BK images from dataset HAM10000. We further compared it with mainstream deep CNN models, such as AlexNet, GoogLeNet, and ResNet, as well as traditional medical image processing algorithms. Our results showed tha

SUBMITTER: Wang L 

PROVIDER: S-EPMC7235884 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature