Evidence map›Paper›PMID 41767621›Full record

ArticleJGH open : an open access journal of gastroenterology and hepatology2026

Computer-Aided Detection-Assisted Colonoscopy Teaches Gaze to Improve Adenoma Detection in First-Year Gastroenterology Fellows.

Nikita Chadha, Marcus Healey, Puneet Puri, HoChong Gilles, Alvin Zfass, Vivek Kaul, Michael Fuchs, Joseph Spataro

Abstract read
In one paragraph

Article in JGH open : an open access journal of gastroenterology and hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

Nikita ChadhaDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.ORCID https://orcid.org/0000-0001-7226-7343
Marcus HealeyDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.
Puneet PuriDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.
HoChong GillesDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.
Alvin ZfassDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.
Vivek KaulDivision of Gastroenterology and Hepatology University of Rochester Medical Center Rochester New York USA.
Michael FuchsDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.
Joseph SpataroDivision of Gastroenterology Richmond Veterans Affairs Medical Center, Central Virginia VA Health Care System Richmond Virginia USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: The impact of computer-aided detection (CADe)-assisted colonoscopy on gastroenterology fellow trainees remains incompletely defined. In this study, adenoma detection rates (ADR) with and without CADe were assessed among gastroenterology fellows. Methods: This quality improvement study compared 1580 colonoscopies performed with and without CADe. The primary outcome was the ADR in fellow-assisted colonoscopies, with and without CADe, stratified by fellowship year. ADRs were compared among procedures assisted by first-year fellows; those assisted by second- and third-year fellows (combined); and those performed by faculty without a fellow. Results: Age, birth sex, race, body mass index, procedure indication, non-neoplastic resection rate, and withdrawal time were similar. CADe-assisted colonoscopy significantly improved the ADR for first-year fellows (66.2% vs. 48.6%, Conclusion: CADe-assisted colonoscopy improved ADR in first-year fellow-assisted procedures. The bounding box created by the system's artificial intelligence may enhance polyp detection by improving peripheral gaze patterns in novice endoscopists. Further studies are needed to validate this hypothesis.

Indexed as

adenoma detection rateartificial intelligencecomputer assisted detection systemendoscopy training

Identifiers

PMID41767621
PMCPMC12945918

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Registered trials

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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.