Evidence map›Paper›PMID 41181544›Full record

ArticleWorld journal of gastrointestinal endoscopy2025

Deep learning meets small-bowel capsule endoscopy: A step toward faster and more consistent diagnosis of obscure gastrointestinal bleeding.

Heng-Rui Liu

Abstract readEditorial
In one paragraph

Article in World journal of gastrointestinal endoscopy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Heng-Rui LiuCancer Research Institute, Jinan University, Guangzhou 510632, Guangdong Province, China. lh@yinuobiomedical.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small-bowel capsule endoscopy (SBCE) is the first-line diagnostic tool for obscure gastrointestinal bleeding but is limited by labor-intensive review, reader dependency, and interobserver variability. In this issue, Kwon

Indexed as

Artificial intelligenceCapsule endoscopyDeep learningLesion detectionObscure gastrointestinal bleeding

Identifiers

PMID41181544
PMCPMC12576623

What OpenQuestion holds

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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.