Evidence map›Paper›PMID 36556092›Full record

ReviewJournal of clinical medicine2022

Artificial Intelligence in Endoscopic Ultrasound for Pancreatic Cancer: Where Are We Now and What Does the Future Entail?

Dushyant Singh Dahiya, Mohammad Al-Haddad, Saurabh Chandan, Manesh Kumar Gangwani, Muhammad Aziz, Babu P Mohan, Daryl Ramai, Andrew Canakis, Jay Bapaye, Neil Sharma

Registry-linked trialAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07381192 (An Artificial Intelligence System for Multimodal, Multi-class Diagnosing Solid Pancreatic Lesions Based on Endoscopic Ultrasound), which is not on this map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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.

NCT07381192 recruitingnot on this mapstarted 2025, after this paper: background citation

An Artificial Intelligence System for Multimodal, Multi-class Diagnosing Solid Pancreatic Lesions Based on Endoscopic Ultrasound

Typeobservational_patient_registrySponsorQilu Hospital of Shandong UniversityRan2025 to 2028Enrolled383ConditionsEndoscopic Ultrasound (EUS), Solid Pancreatic LesionArmsiEUS-SPL(intelligent endoscopic ultrasound system-pancreatic solid lesion)
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Artificial Intelligence in Pancreatic Imaging: A Systematic Review.United European gastroenterology journal · 2025
    Pooled it
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  6. Diagnostic value of endoscopic ultrasound in staging of pancreatic cancer.World journal of gastrointestinal oncology · 2025
    Review
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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

10 authors.

Dushyant Singh DahiyaDepartment of Internal Medicine, Central Michigan University College of Medicine, Saginaw, MI 48601, USA.ORCID 0000-0002-8544-9039
Mohammad Al-HaddadDivision of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Saurabh ChandanDivision of Gastroenterology and Hepatology, CHI Creighton University Medical Center, Omaha, NE 68131, USA.ORCID 0000-0002-2661-6693
Manesh Kumar GangwaniDepartment of Internal Medicine, The University of Toledo Medical Center, Toledo, OH 43614, USA.
Muhammad AzizDepartment of Gastroenterology, The University of Toledo Medical Center, Toledo, OH 43614, USA.
Babu P MohanDivision of Gastroenterology and Hepatology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA.
Daryl RamaiDivision of Gastroenterology and Hepatology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA.
Andrew CanakisDivision of Gastroenterology and Hepatology, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Jay BapayeDepartment of Internal Medicine, Rochester General Hospital, Rochester, NY 14621, USA.
Neil SharmaDivision of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is a highly lethal disease associated with significant morbidity and mortality. In the United States (US), the overall 5-year relative survival rate for pancreatic cancer during the 2012-2018 period was 11.5%. However, the cancer stage at diagnosis strongly influences relative survival in these patients. Per the National Cancer Institute (NCI) statistics for 2012-2018, the 5-year relative survival rate for patients with localized disease was 43.9%, while it was 3.1% for patients with distant metastasis. The poor survival rates are primarily due to the late development of clinical signs and symptoms. Hence, early diagnosis is critical in improving treatment outcomes. In recent years, artificial intelligence (AI) has gained immense popularity in gastroenterology. AI-assisted endoscopic ultrasound (EUS) models have been touted as a breakthrough in the early detection of pancreatic cancer. These models may also accurately differentiate pancreatic cancer from chronic pancreatitis and autoimmune pancreatitis, which mimics pancreatic cancer on radiological imaging. In this review, we detail the application of AI-assisted EUS models for pancreatic cancer detection. We also highlight the utility of AI-assisted EUS models in differentiating pancreatic cancer from radiological mimickers. Furthermore, we discuss the current limitations and future applications of AI technology in EUS for pancreatic cancers.

Indexed as

artificial intelligenceautoimmune pancreatitischronic pancreatitisendoscopic ultrasoundpancreatic cancer

Identifiers

PMID36556092
PMCPMC9786876

What OpenQuestion holds

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Registered trials

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.