Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review.

ABSTRACT:

Background

Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical practice, dermatologists also use other patient data beyond the visual aspects present in a digitized image, further increasing their diagnostic accuracy. Several pilot studies have recently investigated the effects of integrating different subtypes of patient data into CNN-based skin cancer classifiers.

Objective

This systematic review focuses on the current research investigating the impact of merging information from image features and patient data on the performance of CNN-based s

SUBMITTER: Hohn J 

PROVIDER: S-EPMC8285747 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature