ArticleCureus2026
Seeing the Unseen: Artificial Intelligence-Assisted Detection of Subtle Colorectal Adenomas During Colonoscopy.
Article in Cureus, 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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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.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colonoscopy is central to colorectal cancer (CRC) prevention, with adenoma detection rate (ADR) serving as a key quality indicator. Artificial intelligence (AI)-based computer-aided detection (CADe) systems have been developed to assist endoscopists by highlighting subtle mucosal abnormalities during withdrawal. We report the case of a 67-year-old male who underwent AI-assisted colonoscopy for a positive faecal occult blood test, during which CADe prompted the detection and resection of 30 additional polyps not prospectively recognised during conventional white-light inspection. Histopathological analysis demonstrated predominantly tubular adenomas with low-grade dysplasia, as well as a tubulovillous adenoma with focal high-grade dysplasia. This case highlights the potential of CADe to lower the visual threshold for adenoma detection while also illustrating the associated procedural burden and clinical uncertainties surrounding extensive AI-guided lesion detection in routine practice.
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