Association of Clinician Diagnostic Performance With Machine Learning-Based Decision Support Systems: A Systematic Review.

ABSTRACT:

Importance

An increasing number of machine learning (ML)-based clinical decision support systems (CDSSs) are described in the medical literature, but this research focuses almost entirely on comparing CDSS directly with clinicians (human vs computer). Little is known about the outcomes of these systems when used as adjuncts to human decision-making (human vs human with computer).

Objectives

To conduct a systematic review to investigate the association between the interactive use of ML-based diagnostic CDSSs and clinician performance and to examine the extent of the CDSSs' human factors evaluation.

Evidence review

A search of MEDLINE, Embase, PsycINFO, and grey literature was conducted for the period between January 1, 2010, and May 31, 2019. Peer-reviewed studies publ

SUBMITTER: Vasey B 

PROVIDER: S-EPMC7953308 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature