Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.

ABSTRACT:

Objective

To systematically examine the design, reporting standards, risk of bias, and claims of studies comparing the performance of diagnostic deep learning algorithms for medical imaging with that of expert clinicians.

Design

Systematic review.

Data sources

Medline, Embase, Cochrane Central Register of Controlled Trials, and the World Health Organization trial registry from 2010 to June 2019.

Eligibility criteria for selecting studies

Randomised trial registrations and non-randomised studies comparing the performance of a deep learning algorithm in medical imaging with a contemporary group of one or more expert clinicians. Medical imaging has seen a growing interest in deep learning research. The main distinguishing feature of convolutional neural networks (

SUBMITTER: Nagendran M 

PROVIDER: S-EPMC7190037 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature