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2025 ; 25
(1
): 755
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
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English Wikipedia
Artificial intelligence-assisted colonoscopy improves adenoma detection rates in
routine colonoscopy practice: a single-center, retrospective, propensity
score-matched study with concurrent controls
#MMPMID41131470
Ham DY
; Lee JG
; Ahn CI
; Kae SH
; Jang HJ
BMC Gastroenterol
2025[Oct]; 25
(1
): 755
PMID41131470
show ga
BACKGROUND/AIMS: This study aimed to investigate whether a real-time artificial
intelligence (AI)-assisted polyp detection system can improve adenoma detection
rates (ADRs) in real-world colonoscopy practice. METHODS: This single-center,
retrospective, propensity score-matched study collected data from consecutive
patients who underwent colonoscopy-either AI-assisted or standard colonoscopy-
between March 2023 and February 2024. Propensity score matching was conducted to
adjust for baseline characteristics across the groups. RESULTS: During the study
period, 1,085 patients who underwent colonoscopy were eligible for inclusion.
After propensity score matching, 474 patients who underwent AI-assisted
colonoscopy and 474 who underwent standard colonoscopy were included in the
primary analysis. The ADR was significantly higher in the AI-assisted colonoscopy
group than in the standard colonoscopy group (35.9% vs. 26.4%; p?=?0.002).
Additionally, the number of adenomas detected per colonoscopy was significantly
higher in the AI-assisted group than in the standard group (0.69?±?1.22 vs.
0.43?±?0.91; p?0.001). However, the detection rates of advanced adenomas and
sessile serrated lesions did not differ significantly between the two groups.
CONCLUSION: AI-assisted colonoscopy significantly improves ADRs in real-world
colonoscopy practice.