Reporting Guidelines for Artificial Intelligence Studies in Healthcare (for Both Conventional and Large Language Models): What’s New in 2024
Seong Ho Park, Chong Hyun Suh
Abstract
The quality of reporting in research papers, encompassing completeness, clarity, and accuracy, is fundamental for their utility in further research and clinical applications.Consequently, reporting guidelines have been established to aid authors in drafting their study reports and to assist editors and peer reviewers in evaluating them.Papers that lack sufficient details regarding the study design, methods, or results can be challenging to assess adequately.Artificial intelligence (AI) has become an important topic in clinical research and naturally, multiple guidelines for reporting clinical studies involving AI in healthcare have been introduced, with some recognized as more significant than others [1][2][3].Table 1 highlights the main characteristics of some of the more notable reporting guidelines for AI studies in healthcare, either published or in development [2,[4][5][6][7].This brief article aims to provide a concise summary of the key updates to these guidelines for 2024, while also addressing important issues that remain