Reporting guidelines for artificial intelligence in healthcare research

Research output: Contribution to journalReview articlepeer-review

Authors

Colleges, School and Institutes

External organisations

  • University of Birmingham

Abstract

Reporting guidelines are structured tools developed using explicit methodology that specify the minimum information required by researchers when reporting a study. The use of artificial intelligence (AI) reporting guidelines that address potential sources of bias specific to studies involving AI interventions has the potential to improve the quality of AI studies, through improvements in their design and delivery, and the completeness and transparency of their reporting. With a number of guidance documents relating to AI studies emerging from different specialist societies, this Review article provides researchers with some key principles for selecting the most appropriate reporting guidelines for a study involving an AI intervention. As the main determinants of a high-quality study are contained within the methodology of the study design rather than the intervention, researchers are recommended to use reporting guidelines that are specific to the study design, and then supplement them with AI-specific guidance contained within available AI reporting guidelines.

Bibliographic note

© 2021 The Authors. Clinical & Experimental Ophthalmology published by John Wiley & Sons Australia, Ltd on behalf of Royal Australian and New Zealand College of Ophthalmologists.

Details

Original languageEnglish
Pages (from-to)470-476
JournalClinical and Experimental Ophthalmology
Volume49
Issue number5
Early online date6 May 2021
Publication statusPublished - Jul 2021

Keywords

  • artificial intelligence, checklist, guidelines, machine learning, research design, research report