Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes

doi:10.3748/wjg.v31.i40.111499

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Oct 28, 2025 (publication date) through Oct 30, 2025

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastroenterol. Oct 28, 2025; 31(40): 111499
Published online Oct 28, 2025. doi: 10.3748/wjg.v31.i40.111499

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Figure 1 Summary of systematic reviews and meta-analyses assessing artificial intelligence impact on colonoscopy quality metrics[18,37,40,41,43,44,46,48,50-52,57-62,89,108-112]. ¹Advanced adenomas were defined according to current guidelines as size ≥ 10 mm, and/or with villous components > 20%, and/or high-grade dysplasia. CADe: Computer-aided detection; CC: Convetional colonoscopy.

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Figure 2 Artificial intelligence integration in key colonoscopy quality indicators. AI: Artificial intelligence; ADR: Adenoma detection rate; PDR: Polyp detection rate; APC: Adenomas per colonoscopy; AMR: Adenoma miss rate; SSLDR: Sessile serrated lesion detection rate.

Citation: Dimopoulou K, Spinou M, Ioannou A, Nakou E, Zormpas P, Tribonias G. Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes. World J Gastroenterol 2025; 31(40): 111499
URL: https://www.wjgnet.com/1007-9327/full/v31/i40/111499.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i40.111499