Evidence map›Paper›PMID 42369113›Full record

ArticleFrontiers in medicine2026

Advanced computer-aided detection system exhibits no more false positives than experienced endoscopists in an image-based comparative study of colon polyps.

Shan Lei, Guanyu Zhou, Tyler M Berzin, Xun Xiao, Peixi Liu, Pu Wang

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Shan Lei *Department of Gastroenterology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Guanyu Zhou *Department of Gastroenterology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Tyler M Berzin *Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States.
Xun XiaoDepartment of Gastroenterology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Peixi LiuDepartment of Gastroenterology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Pu WangDepartment of Gastroenterology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The presence of computer-aided detection (CADe) false positives (FPs) may pose a hurdle to endoscopists' confidence in, and acceptance of this technology. However, endoscopists also have FPs, which refer to the fact that the object they initially suspected was ultimately confirmed not to be a polyp. The objective of this study was to compare the FPs and overall diagnostic performance between CADe and experienced endoscopists through an image-based study. Methods: We prospectively enrolled 116 consecutive patients undergoing colonoscopy and diagnosed with pathologically confirmed small colon polyp, at Sichuan Provincial People's Hospital. Images of polyps and polyp-free areas in an environment of colon inflation and deflation were taken. Randomly arranged images were labeled by CADe system and a group of experienced endoscopists. Sensitivity, specificity, and accuracy were compared between the CADe system and endoscopists. Results: The study comprised 464 images from 116 polyps and poly-free areas. The CADe system and endoscopists exhibited sensitivity, specificity, and accuracy of 90.09% vs. 87.56% ( Conclusion: The results indicate that a state-of-the-art CADe system exhibits a similar number of FPs as experienced endoscopists, while achieving high polyp sensitivity. Future study efforts to mitigate CADe false-positive distractions should focus not just on minimizing the false-positive rate, but also on educational, behavioral, or user-interface innovations to optimize CADe usability.

Indexed as

artificial intelligencecolonoscopycolon polypcomputer aided detectionfalse positive

Identifiers

PMID42369113
PMCPMC13293802

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