Artificial intelligence-assisted colonoscopy: Transforming detection, characterization, and management of colorectal neoplasia

doi:10.37126/aige.121689

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Artificial Intelligence in Gastrointestinal Endoscopy

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2689-7164

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

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Artif Intell Gastrointest Endosc. Sep 8, 2026; 7(2): 121689
Published online Sep 8, 2026. doi: 10.37126/aige.121689

Table 2 Comparative table of the use of artificial intelligence in the characterization of colorectal neoplasms

Ref.	Design	AI vs comparator	Diagnostic accuracy (AI vs human)	P value	Sensitivity (%)	Specificity (%)
Byrne et al[23]	Prospective real-time	AI vs expert endoscopists	94% vs 91%	0.16	98	83
Kudo et al[24]	Multicenter diagnostic	AI vs histology	98.0% (stained)/96.0% (NBI)	Not reported	96.9	94-100
Mori et al[25]	Prospective	AI vs expert endoscopists	92% vs 80%-85%	> 0.05	98	83

AI: Artificial intelligence; NBI: Narrow-band imaging.

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Citation: Aliaga Ramos J. Artificial intelligence-assisted colonoscopy: Transforming detection, characterization, and management of colorectal neoplasia. Artif Intell Gastrointest Endosc 2026; 7(2): 121689
URL: https://www.wjgnet.com/2689-7164/full/v7/i2/121689.htm
DOI: https://dx.doi.org/10.37126/aige.121689

Aliaga Ramos J. Artificial intelligence-assisted colonoscopy: Transforming detection, characterization, and management of colorectal neoplasia. Artif Intell Gastrointest Endosc 2026; 7(2): 121689 [DOI: 10.37126/aige.121689]

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