Evidence map›Paper›PMID 39941748›Full record

ReviewCancers2025

Impact of Artificial Intelligence on Pancreaticobiliary Endoscopy.

Aryan Jain, Mayur Pabba, Aditya Jain, Sahib Singh, Hassam Ali, Rakesh Vinayek, Ganesh Aswath, Neil Sharma, Sumant Inamdar, Antonio Facciorusso

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Artificial intelligence in pancreatic cancer: applications in early detection, tumor staging, and survival prediction-a comprehensive review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  2. Review
  3. Article
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

10 authors.

Aryan JainDepartment of Gastroenterology, Albany Medical College, Albany, NY 12208, USA.
Mayur PabbaDepartment of Gastroenterology, Albany Medical College, Albany, NY 12208, USA.ORCID 0009-0004-7620-3389
Aditya JainDepartment of Gastroenterology, Albany Medical College, Albany, NY 12208, USA.
Sahib SinghDepartment of Internal Medicine, Sinai Hospital of Baltimore, Baltimore, MD 21215, USA.
Hassam AliDepartment of Gastroenterology, ECU Health Medical Center/Brody School of Medicine, Greenville, NC 27834, USA.
Rakesh VinayekDepartment of Gastroenterology, Sinai Hospital of Baltimore, Baltimore, MD 21215, USA.
Ganesh AswathDepartment of Gastroenterology, State University of New York Upstate Medical University, Syracuse, NY 13210, USA.
Neil SharmaDepartment of Gastroenterology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Sumant InamdarDepartment of Gastroenterology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
Antonio FacciorussoGastroenterology Unit, Department of Experimental Medicine, University of Salento, 73100 Lecce, Italy.ORCID 0000-0002-2107-2156

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreaticobiliary diseases can lead to significant morbidity and their diagnoses rely on imaging and endoscopy which are dependent on operator expertise. Artificial intelligence (AI) has seen a rapid uptake in the field of luminal endoscopy, such as polyp detection during colonoscopy. However, its use for pancreaticobiliary endoscopic modalities such as endoscopic ultrasound (EUS) and cholangioscopy remains scarce, with only few studies available. In this review, we delve into the current evidence, benefits, limitations, and future scope of AI technologies in pancreaticobiliary endoscopy.

Indexed as

artificial intelligencebiliary stricturescholangiocarcinomacholangioscopydata privacydiagnostic accuracyendoscopic ultrasoundethical considerationspancreatic lesionspancreaticobiliary disorders

Identifiers

PMID39941748
PMCPMC11815774

What OpenQuestion holds

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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.