Evidence map›Paper›PMID 42732356›Full record

ArticleGastroenterology report2026

Real-time AI assistance improves adherence to standardized biliopancreatic EUS examination: a real-world comparative study.

Chenxia Zhang, Jun Zhang, Wei Tan, Xiao Tao, Wei Zhou, Bing Xiao, Honggang Yu

Abstract read
In one paragraph

Article in Gastroenterology report, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chenxia ZhangDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
Jun ZhangDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
Wei TanDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
Xiao TaoDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
Wei ZhouDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
Bing XiaoDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
Honggang YuDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Biliopancreatic endoscopic ultrasound (EUS) is highly operator-dependent, and adherence to standardized examination pathways may vary in routine practice. Evidence on whether real-time artificial intelligence (AI) assistance improves adherence to standardized biliopancreatic EUS examination in real-world settings remains limited. Methods: We conducted a retrospective comparative cohort study at a tertiary referral center to evaluate the real-world implementation of a real-time AI assistance system during biliopancreatic EUS. Examinations from the pre-AI period were compared with those from the post-AI period after a washout interval. Propensity score matching and interrupted time-series analysis were used to reduce baseline imbalance and assess temporal changes. The primary outcome was adherence to the standardized examination protocol, operationalized as total documentation completeness across eight predefined anatomical stations. Secondary outcomes included station-level adherence and lesion detection, with prespecified evaluation of pancreatic masses smaller than 2 cm. Results: Among 1,465 eligible examinations, 854 matched examinations (427 per group) were analyzed. Adherence to the standardized eight-station examination was higher in the post-AI group, reflected by greater total documentation completeness (89.93% vs 81.29%, adjusted absolute difference 8.65%, 95% confidence interval [CI] 6.58-10.71, Conclusions: In this real-world comparative study, real-time AI assistance was associated with greater adherence to a standardized biliopancreatic EUS examination protocol and a higher observed detection rate of pancreatic masses smaller than 2 cm. These findings suggest that real-time AI assistance may facilitate more standardized biliopancreatic EUS examination in routine practice.

Indexed as

artificial intelligencebiliopancreatic diseasesendoscopic ultrasoundstandardization

Identifiers

PMID42732356
PMCPMC13570796

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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.