Advances in artificial intelligence-based colonoscopic tools and modalities: Transforming colorectal cancer detection and management

Table 1 Summary of systematic reviews and meta-analyses evaluating the impact of artificial intelligence-assisted colonoscopy on adenoma detection rate

Ref.	Study type	Number of studies/participants	Main outcomes	Key findings
Khalaf et al[10], 2025	Systematic review and meta-analysis	7 RCTs/5427 participants	ADR, PDR	AI-assisted colonoscopy significantly increased ADR and PDR. Most additional lesions detected were small polyps, while detection of advanced adenomas and pedunculated lesions was lower
Huang et al[15], 2022	Meta-analysis	10 RCTs/6629 participants	ADR, PDR, lesions per colonoscopy	AI significantly improved ADR and PDR. Higher numbers of adenomas, polyps, and sessile serrated lesions were detected per colonoscopy, with benefits across most lesion sizes and locations except pedunculated lesions and cecal lesions
Makar et al[11], 2025	Updated meta-analysis	28 RCTs/23861 participants	ADR, adenoma miss rate	CADe increased ADR by approximately 20% and reduced adenoma miss rates by 55%. Benefits were consistent across platforms, endoscopist experience levels, and clinical settings
Hassan et al[16], 2021	Meta-analysis	5 RCTs/4354 participants	ADR	CADe consistently demonstrated benefit (36.6% vs 25.2%) compared with conventional colonoscopy, with improvements across different lesion sizes, morphologies, and anatomical locations
Hassan et al[12], 2023	Systematic review and meta-analysis	21 RCTs/18232 participants	ADR, adenoma miss rate	CADe-assisted colonoscopy significantly increased ADR (44.0% vs 35.9%) and reduced adenoma miss rates compared with standard colonoscopy
Soleymanjahi et al[13], 2024	Systematic review and meta-analysis	44 RCTs/36201 participants	ADR, adenomas per colonoscopy	CADe was associated with increased detection and increased the average number of adenomas detected per colonoscopy
Adiwinata et al[17], 2023	Systematic review and meta-analysis	Multiple studies	ADR	AI-assisted colonoscopy significantly improved ADR with a pooled odds ratio of 1.58, confirming a clear detection advantage over conventional colonoscopy

AI: Artificial intelligence; ADR: Adenoma detection rate; PDR: Polyp detection rate; RCTs: Randomised controlled trials; CADe: Computer-aided detection.

Table 2 Summary of randomized controlled trials assessing the clinical performance of artificial intelligence-assisted colonoscopy

Ref.	Study design	Participants	AI system/intervention	Main outcomes	Key findings
Repici et al[23], 2020	Multicenter randomized trial	685 patients	GI-genius CADe system	ADR, adenomas per colonoscopy	AI-assisted colonoscopy significantly increased ADR (54.8% vs 40.4%) and adenomas detected per colonoscopy, mainly due to improved detection of small adenomas ≤ 9 mm without increasing withdrawal time
Seager et al[24], 2024	Multicenter randomized control trial (COLO-DETECT trial)	Not specified in text	GI-genius CADe system	ADR, adenomas per procedure	AI significantly improved ADR (56.6% vs 48.4%) and mean adenomas per procedure without increasing adverse events
Nakashima et al[25], 2023	Randomized trial	415 patients	CADe-assisted colonoscopy	ADR, adenoma miss rate	Computer-aided detection improved ADR (59.4% vs 47.6%) and reduced adenoma miss rates in the rectosigmoid colon without prolonging examination time
Wang et al[26], 2020	Double-blind randomized trial	962 patients	CADe system	ADR	ADR significantly improved (34% vs 28%). AI particularly enhanced detection of subtle lesions such as small, flat, or partially hidden polyps
Lau et al[27], 2024	Randomized trial	766 patients	Computer-aided detection -assisted colonoscopy	ADR	CADe significantly increased ADR among endoscopists-in-training and improved detection of small adenomas in both right and left colon
Xu et al[28], 2021	Randomized trial	2352 patients	AI-assisted colonoscopy	Polyps per colonoscopy	AI increased detection of additional polyps per colonoscopy and improved identification of diminutive and flat lesions
Glissen Brown et al[29], 2022	Tandem colonoscopy randomized contral trial	Not specified in text	CADe-system	Adenoma miss rate	CADe significantly reduced adenoma miss rate (20.1% vs 31.3%) and increased adenomas detected per colonoscopy
Luo et al[30], 2021	Randomized back-to-back colonoscopy study	150 patients	Real-time AI polyp detection system	PDR	AI significantly improved polyp detection rate, mainly through improved detection of diminutive polyps

AI: Artificial intelligence; ADR: Adenoma detection rate; PDR: Polyp detection rate; CADe: Computer-aided detection; GI: Gastrointestinal.