{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T06:18:59Z","timestamp":1783491539541,"version":"3.55.0"},"reference-count":38,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T00:00:00Z","timestamp":1783468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Res. Metr. Anal."],"abstract":"<jats:p>Fraudulent, falsified, and otherwise unreliable clinical research threatens the foundations of evidence-based medicine because systematic reviews, meta-analyses, and clinical practice guidelines depend on the trustworthiness of the studies they include. Retractions are increasing faster than publication output and often occur only after substantial delay, allowing problematic trials to be cited, pooled, and incorporated into downstream clinical recommendations. Recent evidence shows that retracted randomized trials have contaminated thousands of meta-analyses and hundreds of guideline documents, while only a small minority of affected reviews later self-correct. This is not only a clinical problem but also an integrity analytics problem: unreliable studies generate article-level, trial-level, and network-level signals that are not yet systematically integrated into evidence-synthesis workflows. Existing approaches can detect some image anomalies, textual irregularities, reporting inconsistencies, and statistical red flags, but important blind spots remain. Fabricated clinical datasets may appear statistically plausible, outcome switching often requires registration-publication comparison, and most available tools operate in isolation rather than as coordinated screening systems. We argue that the next generation of safeguards should combine AI\/ML-based detection systems, statistical forensic methods, structured trustworthiness appraisal tools, and workflow-level screening frameworks within evidence synthesis. Embedding staged trustworthiness assessment early in systematic reviews, alongside stronger publisher- and database-level integrity infrastructure, could help prevent unreliable trials from distorting pooled estimates and downstream guidance. Such systems should support triage and prioritization rather than replace human judgment. Framed in this way, scalable trustworthiness assessment represents a practical research metrics and analytics agenda for strengthening the evidence ecosystem from primary studies to reviews, guidelines, and policy decisions.<\/jats:p>","DOI":"10.3389\/frma.2026.1833223","type":"journal-article","created":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T05:58:00Z","timestamp":1783490280000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence to enhance research integrity in evidence-based medicine: toward scalable trustworthiness assessment"],"prefix":"10.3389","volume":"11","author":[{"given":"Moses","family":"Mo","sequence":"first","affiliation":[{"name":"Cumming School of Medicine, University of Calgary","place":["Calgary, AB, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rohit","family":"Arora","sequence":"additional","affiliation":[{"name":"Harvard University","place":["Cambridge, MA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Cao","sequence":"additional","affiliation":[{"name":"University of Toronto","place":["Toronto, ON, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea C.","family":"Tricco","sequence":"additional","affiliation":[{"name":"Unity Health Toronto","place":["Toronto, ON, Canada"]},{"name":"Li Ka Shing Knowledge Institute, St. Michael's Hospital","place":["Toronto, ON, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Moher","sequence":"additional","affiliation":[{"name":"Centre for Implementation Research, Ottawa Hospital Research Institute","place":["Ottawa, ON, Canada"]},{"name":"School of Epidemiology and Public Health, University of Ottawa","place":["Ottawa, ON, Canada"]},{"name":"Dalla Lana School of Public Health, University of Toronto","place":["Toronto, ON, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,8]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1080\/08989621.2022.2082290","article-title":"A randomized trial alerting authors, with or without coauthors or editors, that research they cited in systematic reviews and guidelines has been retracted","volume":"31","author":"Avenell","year":"2024","journal-title":"Account. 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Sci."},{"key":"B12","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1186\/s13063-019-3173-2","article-title":"COMPare: a prospective cohort study correcting and monitoring 58 misreported trials in real time","volume":"20","author":"Goldacre","year":"2019","journal-title":"Trials"},{"key":"B13","unstructured":"Recovering data from summary statistics: Sample Parameter Reconstruction via Iterative TEchniques (SPRITE)\n          \n          \n            \n              Heathers\n              J. A.\n            \n            \n              Anaya\n              J.\n            \n            \n              van der Zee\n              T.\n            \n            \n              Brown\n              N. J.\n            \n          \n          PeerJ Inc.\n          \n          2018"},{"key":"B14","unstructured":"Image Analysis AI Software for Research | Imagetwin\n          \n          2026"},{"key":"B15","unstructured":"Science-wide mapping and ranking of institutions based on affiliated authors\n          \n          \n            \n              Ioannidis\n              J. P. A.\n            \n            \n              Baas\n              J.\n            \n            \n              Boverhof\n              R.\n            \n            \n              Voyant\n              C.\n            \n          \n          bioRxiv [Preprint]"},{"key":"B16","doi-asserted-by":"publisher","first-page":"e3002999","DOI":"10.1371\/journal.pbio.3002999","article-title":"Linking citation and retraction data reveals the demographics of scientific retractions among highly cited authors","volume":"23","author":"Ioannidis","year":"","journal-title":"PLoS Biol"},{"key":"B17","unstructured":"Retracted randomized trials attributed to super-retractors and top-cited scientists with multiple retractions: secondary analysis of the VITALITY retrospective cohort\n          \n          \n            \n              Lyu\n              C.\n            \n            \n              Matbouriahi\n              M.\n            \n            \n              Naudet\n              F.\n            \n            \n              Ioannidis\n              J. 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W.\n            \n          \n          A look back at 2024 at Retraction Watch, and Forward to 2025.\n          \n          2024"},{"key":"B31","doi-asserted-by":"publisher","first-page":"e68397","DOI":"10.1371\/journal.pone.0068397","article-title":"Why has the number of scientific retractions increased?","volume":"8","author":"Steen","year":"2013","journal-title":"PLoS ONE"},{"key":"B32","unstructured":"2026"},{"key":"B33","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1038\/d41586-023-03464-x","article-title":"How big is science's fake-paper problem?","volume":"623","author":"Van Noorden","year":"","journal-title":"Nature"},{"key":"B34","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1038\/d41586-023-03974-8","article-title":"More than 10,000 research papers were retracted in 2023 \u2014 a new record","volume":"624","author":"Van Noorden","year":"","journal-title":"Nature"},{"key":"B35","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1002\/jrsm.1599","article-title":"Identifying and managing problematic trials: a Research Integrity Assessment (RIA) tool for randomized controlled trials in evidence synthesis","volume":"14","author":"Weibel","year":"2023","journal-title":"Res. 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