Unassisted Clinicians Versus Deep Learning-Assisted Clinicians in Image-Based Cancer Diagnostics: Systematic Review With Meta-analysis.

ABSTRACT:

Background

A number of publications have demonstrated that deep learning (DL) algorithms matched or outperformed clinicians in image-based cancer diagnostics, but these algorithms are frequently considered as opponents rather than partners. Despite the clinicians-in-the-loop DL approach having great potential, no study has systematically quantified the diagnostic accuracy of clinicians with and without the assistance of DL in image-based cancer identification.

Objective

We systematically quantified the diagnostic accuracy of clinicians with and without the assistance of DL in image-based cancer identification.

Methods

PubMed, Embase, IEEEXplore, and the Cochrane Library were searched for studies published between January 1, 2012, and December 7, 2021. Any type of stud

SUBMITTER: Xue P 

PROVIDER: S-EPMC10020907 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature