Transparency in Artificial Intelligence Reporting in Ophthalmology-A Scoping Review.

ABSTRACT:

Topic

This scoping review summarizes artificial intelligence (AI) reporting in ophthalmology literature in respect to model development and validation. We characterize the state of transparency in reporting of studies prospectively validating models for disease classification.

Clinical relevance

Understanding what elements authors currently describe regarding their AI models may aid in the future standardization of reporting. This review highlights the need for transparency to facilitate the critical appraisal of models prior to clinical implementation, to minimize bias and inappropriate use. Transparent reporting can improve effective and equitable use in clinical settings.

Methods

Eligible articles (as of January 2022) from PubMed, Embase, Web of Science, and CINAHL

SUBMITTER: Chen D 

PROVIDER: S-EPMC11000111 | biostudies-literature | 2024 Jul-Aug

REPOSITORIES: biostudies-literature