Quality assessment standards in artificial intelligence diagnostic accuracy systematic reviews: a meta-research study.

ABSTRACT: Artificial intelligence (AI) centred diagnostic systems are increasingly recognised as robust solutions in healthcare delivery pathways. In turn, there has been a concurrent rise in secondary research studies regarding these technologies in order to influence key clinical and policymaking decisions. It is therefore essential that these studies accurately appraise methodological quality and risk of bias within shortlisted trials and reports. In order to assess whether this critical step is performed, we undertook a meta-research study evaluating adherence to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool within AI diagnostic accuracy systematic reviews. A literature search was conducted on all studies published from 2000 to December 2020. Of 50 included reviews, 36

SUBMITTER: Jayakumar S 

PROVIDER: S-EPMC8795185 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature