Artificial Intelligence in Cardiovascular Clinical Trials

医学 临床试验 重症监护医学 内科学
作者
Jonathan W. Cunningham,William T. Abraham,Ankeet S. Bhatt,Jessilyn Dunn,G. Michael Felker,Sneha S. Jain,Christopher J. Lindsell,Michelle Mace,Trejeeve Martyn,Rashmee U. Shah,Geoffrey H. Tison,Tala Fakhouri,Mitchell A. Psotka,Harlan M. Krumholz,Mona Fiuzat,Christopher M. O’Connor,Scott D. Solomon
出处
期刊:Journal of the American College of Cardiology [Elsevier]
卷期号:84 (20): 2051-2062 被引量:4
标识
DOI:10.1016/j.jacc.2024.08.069
摘要

Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technologies can potentially automate and streamline clinical trial operations. This review describes opportunities to integrate AI throughout a trial's life cycle, including designing the trial, identifying eligible patients, obtaining informed consent, ascertaining physiological and clinical event outcomes, interpreting imaging, and analyzing or disseminating the results. Nevertheless, AI poses risks, including generating inaccurate results, amplifying biases against underrepresented groups, and violating patient privacy. Medical journals and regulators are developing new frameworks to evaluate AI research tools and the data they generate. Given the high-stakes role of randomized trials in medical decision making, AI must be integrated carefully and transparently to protect the validity of trial results.

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