Evidence map›Paper›PMID 41700159›Full record

ReviewWorld journal of gastrointestinal endoscopy2026

Harnessing artificial intelligence in gastrointestinal endoscopy for early detection of dysplastic lesions in inflammatory bowel disease.

Dusan D Popovic, Milica Dragovic, Natasa Panic, Marija Marjanovic-Haljilji, Tijana Glisic, Snezana Lukic, Dragana Mijac, Jelena Bogdanovic, Ljiljana Bogdanović, Aleksandra Djokovic and 2 more

Abstract readReview
In one paragraph

Review in World journal of gastrointestinal endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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. 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

12 authors.

Dusan D PopovicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Milica DragovicDepartment of Gastroenterology and Hepatology, Clinic for Internal Medicine, University Clinical Hospital Center "Dr. Dragisa Misovic-Dedinje", Belgrade 11000, Beograd, Serbia.
Natasa PanicDepartment of Gastroenterology and Hepatology, Clinic for Internal Medicine, University Clinical Hospital Center "Dr. Dragisa Misovic-Dedinje", Belgrade 11000, Beograd, Serbia.
Marija Marjanovic-HaljiljiDepartment of Gastroenterology and Hepatology, Clinic for Internal Medicine, University Clinical Hospital Center "Dr. Dragisa Misovic-Dedinje", Belgrade 11000, Beograd, Serbia.
Tijana GlisicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Snezana LukicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Dragana MijacFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Jelena BogdanovicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Ljiljana BogdanovićFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Aleksandra DjokovicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Ana StarcevicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.
Branka FilipovicFaculty of Medicine, University of Belgrade, Belgrade 11000, Beograd, Serbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has become an increasingly valuable tool in gastrointestinal endoscopy, especially in the context of inflammatory bowel disease, including ulcerative colitis and Crohn's disease. One of its most impactful applications is the early detection and accurate characterization of dysplastic lesions, which are often difficult to identify owing to chronic inflammation and mucosal alterations. AI-based systems, such as computer-aided detection and computer-aided diagnosis, have shown excellent performance in identifying subtle or flat lesions, improving the quality and consistency of dysplasia surveillance, and aiding in colorectal cancer prevention. In addition to neoplasia detection, AI plays a significant role in assessing mucosal inflammation and disease activity by offering objective scoring, reducing interobserver variability, and even predicting histological remission without the need for biopsy. These capabilities enhance decision-making and support a more personalized approach to patient management. While technical, regulatory, and integration challenges remain, current evidence supports the growing role of AI in improving both diagnostic precision and long-term outcomes in inflammatory bowel disease endoscopy.

Indexed as

Artificial intelligenceColorectal cancer surveillanceComputer-aided detectionComputer-aided diagnosisCrohn’s diseaseDysplasiaEndoscopyInflammatory bowel diseaseUlcerative colitis

Identifiers

PMID41700159
PMCPMC12906226

What OpenQuestion holds

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LicenceCC BY-NC
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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.