ArticleMedicine2022
Effects of ai-assisted colonoscopy on adenoma miss rate/adenoma detection rate: A protocol for systematic review and meta-analysis.
Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 12 citations in OpenAlex.
- Improving Colorectal Cancer Detection with AI-Assisted Colonoscopy: A Systematic Review and Meta-Analysis of 38 RCTs with GRADE Assessment.Journal of gastrointestinal cancer · 2025Pooled it
- Artificial intelligence for reducing missed detection of adenomas and polyps in colonoscopy: A systematic review and meta-analysis.World journal of gastroenterology · 2025Pooled it
- One in three adenomas could be missed by white-light colonoscopy - findings from a systematic review and meta-analysis.BMC gastroenterology · 2025Pooled it
- Artificial Intelligence in Radiology: Hidden Fragilities and the Path to Resilience.Saudi medical journal · 2026Review
- Artificial Intelligence in Gastrointestinal Endoscopy: Current Advances, Clinical Integration, and Future Directions: A Narrative Review.Clinical and experimental gastroenterology · 2026Review
- Evaluation of Perceptual Realism and Clinical Plausibility of AI-Generated Colon Polyp Images.Biomedicines · 2025Article
- Artificial intelligence-assisted colonoscopy for colorectal lesion detection: a case-control study on diagnostic accuracy and histopathological agreement.Arquivos brasileiros de cirurgia digestiva : ABCD = Brazilian archives of digestive surgery · 2025Article
- Artificial intelligence for colorectal neoplasia detection during colonoscopy: a systematic review and meta-analysis of randomized clinical trials.EClinicalMedicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColonoscopy can detect colorectal adenomas and reduce the incidence of colorectal cancer, but there are still many missing diagnoses. Artificial intelligence-assisted colonoscopy (AIAC) can effectively reduce the rate of missed diagnosis and improve the detection rate of adenoma, but its clinical application is still unclear. This systematic review and meta-analysis assessed the adenoma missed detection rate (AMR) and the adenoma detection rate (ADR) by artificial colonoscopy.
methodsConduct a comprehensive literature search using the PubMed, Medline database, Embase, and the Cochrane Library. This meta-analysis followed the direction of the preferred reporting items for systematic reviews and meta-analyses, the preferred reporting item for systematic review and meta-analysis. The random effect model was used for meta-analysis.
resultsA total of 12 articles were eventually included in the study. Computer aided detection (CADe) significantly decreased AMR compared with the control group (137/1039, 13.2% vs 304/1054, 28.8%; OR,0.39; 95% CI, 0.26-0.59; P < .05). Similarly, there was statistically significant difference in ADR between the CADe group and control group, respectively (1835/5041, 36.4% vs 1309/4553, 28.7%; OR, 1.54; 95% CI, 1.39-1.71; P < .05). The advanced adenomas missed rate and detection rate in CADe group was not statistically significant when compared with the control group.
conclusionsAIAC can effectively reduce AMR and improve ADR, especially small adenomas. Therefore, this method is worthy of clinical application. However, due to the limitations of the number and quality of the included studies, more in-depth studies are needed in the field of AIAC in the future.
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Registered trials
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.