Abstract
AbstractThe integration of Artificial Intelligence (AI) technologies into clinical practice holds significant promise for revolutionizing healthcare. However, the realization of this potential requires rigorous evaluation and validation of AI applications to ensure their safety, efficacy, and clinical significance. Despite increasing awareness of the need for robust testing, the majority of AI-related Randomized Controlled Trials (RCTs) so far have exhibited notable limitations, impeding the generalizability and proper integration of their findings into clinical settings. To understand whether the field is progressing towards more robust testing, we conducted an analysis of the registration data of ongoing and planned RCTs of AI in medicine available in theClinicaltrials.govdatabase. Our analysis highlights several key trends and challenges. Effectively addressing these challenges is essential for advancing the field of medical AI and ensuring its successful integration into clinical practice.
Publisher
Cold Spring Harbor Laboratory