Evidence map›Paper›PMID 40438910›Full record

ReviewClinical endoscopy2025

Clinical significance of computer-aided quality assessment systems in colonoscopy: a comprehensive review.

Wai Phyo Lwin, Katsuro Ichimasa, Shin-Ei Kudo, Yuta Kouyama, Taishi Okumura, Yasuharu Maeda, Yutaro Ide, Khay Guan Yeoh, Masashi Misawa

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical endoscopy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Ethical and Legal Implications of Implementing AI in Gastrointestinal Endoscopy.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026
    Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Wai Phyo LwinDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Katsuro IchimasaDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Shin-Ei KudoDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Yuta KouyamaDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Taishi OkumuraDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Yasuharu MaedaDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Yutaro IdeDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Khay Guan YeohYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Masashi MisawaDigestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colonoscopy is the primary tool for colorectal cancer screening. High-quality colonoscopy is crucial for the detection of precancerous adenomas; however, the adenoma detection rate varies depending on the skill and experience of the endoscopist. Computer-aided quality assessment (CAQ) uses artificial intelligence (AI) technology to evaluate the quality of colonoscopy examinations. It plays an important role in reducing variations in examination quality and obtaining high-quality colonoscopic images. In this review, we focus specifically on the speedometer, effective withdrawal time, fold examination quality, bowel preparation quality assessment, and cecal intubation with CAQ systems and discuss the role and effectiveness of these systems. CAQ systems are expected to contribute to increase in adenoma detection rates, improvement in endoscopist skills, and standardization of examination quality. However, challenges such as variability in AI performance across different clinical settings and potential overreliance on automated prompts remain key limitations.

Indexed as

AdenomaArtificial intelligenceColonic polypsColonoscopyComputer-assisted diagnosis

Identifiers

PMID40438910
PMCPMC12489550

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.