SynthesisBMC medical imaging2026
Effectiveness of artificial intelligence-assisted colonoscopy for colorectal lesion detection: a systematic review and meta-analysis of randomized controlled trials.
Synthesis in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
Funding
Abstract
backgroundColonoscopy is the gold standard for colorectal cancer detection and prevention, but its performance depends on operator skill and lesion features. Artificial intelligence (AI)-assisted colonoscopy has been introduced to improve adenoma detection.
methodsA comprehensive search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, ClinicalTrials.gov, and major Chinese databases to identify randomized controlled trials (RCTs) comparing AI-assisted and conventional colonoscopy. Meta-analyses were performed using Review Manager 5.4 and Stata 14.0. The quality of evidence was graded using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system, while trial sequential analysis (TSA) was applied to assess the robustness and information sufficiency of the results.
resultsA total of 46 RCTs encompassing 37,012 participants were included. Compared with conventional colonoscopy, AI-assisted colonoscopy was associated with a higher ADR (RR = 1.22, 95% CI = 1.17-1.27, P < 0.00001), polyp detection rate (PDR: RR = 1.22, 95% CI = 1.16-1.29, P < 0.00001), polyp detection per colonoscopy (PPC: MD = 0.28, 95% CI = 0.21-0.36), and adenoma detection per colonoscopy (APC: MD = 0.22, 95% CI = 0.15-0.29). The detection rate of sessile serrated lesions (SSL) was also higher in the AI-assisted group (RR = 1.20, 95% CI: 1.05-1.36, P = 0.007), whereas no significant difference was observed in advanced adenoma detection rate (AADR).
conclusionsAI-assisted colonoscopy was associated with improvements in several detection-related quality indicators, including ADR, PDR, PPC, APC, and SSL detection rate. However, given the very low GRADE certainty for ADR and PDR and the lack of long-term outcome data, these findings should be interpreted cautiously. CLINICAL TRIAL NUMBER: Not applicable.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.