Randomized Controlled Trials of Artificial Intelligence in Clinical Practice: Systematic Review

• Published in: Journal of medical Internet research Vol. 24; no. 8; p. e37188
• Main Authors: Lam, Thomas Y T, Cheung, Max F K, Munro, Yasmin L, Lim, Kong Meng, Shung, Dennis, Sung, Joseph J Y
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 25.08.2022; Gunther Eysenbach MD MPH, Associate Professor; JMIR Publications
• Subjects: Anesthesiology; Artificial Intelligence; Bias; Cardiology; Clinical medicine; Clinical trials; Deep learning; Diabetes; Endoscopy; Europe; Generalizability; Health care management; Humans; Hypertension; Intelligence; Intervention; Machine learning; Mammography; Measurement; Mortality; Neural networks; North America; Patients; Randomized Controlled Trials as Topic; Review; Smartphones; Subject heading schemes; Systematic review; Tumors; North America; Europe; United States > US; China; clinical; clinical informatics; mobile phone; gastroenterology; systematic review; artificial intelligence; randomized controlled trial
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/37188

The number of artificial intelligence (AI) studies in medicine has exponentially increased recently. However, there is no clear quantification of the clinical benefits of implementing AI-assisted tools in patient care. This study aims to systematically review all published randomized controlled trials (RCTs) of AI-assisted tools to characterize their performance in clinical practice. CINAHL, Cochrane Central, Embase, MEDLINE, and PubMed were searched to identify relevant RCTs published up to July 2021 and comparing the performance of AI-assisted tools with conventional clinical management without AI assistance. We evaluated the primary end points of each study to determine their clinical relevance. This systematic review was conducted following the updated PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Among the 11,839 articles retrieved, only 39 (0.33%) RCTs were included. These RCTs were conducted in an approximately equal distribution from North America, Europe, and Asia. AI-assisted tools were implemented in 13 different clinical specialties. Most RCTs were published in the field of gastroenterology, with 15 studies on AI-assisted endoscopy. Most RCTs studied biosignal-based AI-assisted tools, and a minority of RCTs studied AI-assisted tools drawn from clinical data. In 77% (30/39) of the RCTs, AI-assisted interventions outperformed usual clinical care, and clinically relevant outcomes improved with AI-assisted intervention in 70% (21/30) of the studies. Small sample size and single-center design limited the generalizability of these studies. There is growing evidence supporting the implementation of AI-assisted tools in daily clinical practice; however, the number of available RCTs is limited and heterogeneous. More RCTs of AI-assisted tools integrated into clinical practice are needed to advance the role of AI in medicine. PROSPERO CRD42021286539; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=286539.