Randomised controlled trials evaluating artificial intelligence in clinical practice: a scoping review.

Journal: The Lancet. Digital health
Published Date: May 1, 2024

Abstract

This scoping review of randomised controlled trials on artificial intelligence (AI) in clinical practice reveals an expanding interest in AI across clinical specialties and locations. The USA and China are leading in the number of trials, with a focus on deep learning systems for medical imaging, particularly in gastroenterology and radiology. A majority of trials (70 [81%] of 86) report positive primary endpoints, primarily related to diagnostic yield or performance; however, the predominance of single-centre trials, little demographic reporting, and varying reports of operational efficiency raise concerns about the generalisability and practicality of these results. Despite the promising outcomes, considering the likelihood of publication bias and the need for more comprehensive research including multicentre trials, diverse outcome measures, and improved reporting standards is crucial. Future AI trials should prioritise patient-relevant outcomes to fully understand AI's true effects and limitations in health care.

Authors

  • Ryan Han
    Department of Computer Science, Stanford University, Stanford, USA.
  • Julián N Acosta
    From the Department of Neurology, Yale School of Medicine, New Haven, Conn (J.N.A., G.J.F.); and Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115 (P.R.).
  • Zahra Shakeri
    Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
  • John P A Ioannidis
    Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, California.
  • Eric J Topol
    Scripps Research Translational Institute, La Jolla, CA 92037, USA; Scripps Clinic Division of Cardiovascular Diseases, La Jolla, CA 92037, USA. Electronic address: etopol@scripps.edu.
  • Pranav Rajpurkar
    Harvard Medical School, Department of Biomedical Informatics, Cambridge, MA, 02115, US.

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