Evidence map›Paper›PMID 41560382›Full record

ArticleYonsei medical journal2026

Endoscopic Diagnosis of Eosinophilic Esophagitis Using a Multi-Task U-Net: A Pilot Study.

Ga Hee Kim, Jooyoung Park, Seungju Park, Jeongeun Hwang, Jisup Lim, Kanggil Park, Sunghwan Ji, Kwangbeom Park, Jun-Young Seo, Jin Hee Noh and 4 more

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In one paragraph

Article in Yonsei medical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

14 authors.

Ga Hee Kim *Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-7652-2580
Jooyoung Park *Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0002-7641-3827
Seungju ParkCHA University School of Medicine, Seongnam, Korea.ORCID https://orcid.org/0000-0002-5944-6344
Jeongeun HwangDepartment of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, Cheonan, Korea.ORCID https://orcid.org/0000-0002-5821-5405
Jisup LimDepartment of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0001-8938-233X
Kanggil ParkDepartment of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0009-0009-5525-3869
Sunghwan JiDivision of Geriatrics, Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0002-8150-933X
Kwangbeom ParkDepartment of Internal Medicine, Nowon Eulji Medical Center, Eulji University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-3826-3274
Jun-Young SeoDepartment of Internal Medicine, Bundang Jesaeng General Hospital, Seongnam, Korea.ORCID https://orcid.org/0000-0002-4987-0686
Jin Hee NohDepartment of Internal Medicine, Hallym University College of Medicine, Hallym University Sacred Heart Hospital, Anyang, Korea.ORCID https://orcid.org/0000-0001-6720-9528
Ji Yong AhnDepartment of Gastroenterology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0002-0030-3744
Jeong-Sik ByeonDepartment of Gastroenterology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0002-9793-6379
Do Hoon KimDepartment of Gastroenterology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea. dohoon.md@gmail.com.ORCID https://orcid.org/0000-0002-4250-4683
Namkug KimDepartment of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0002-3438-2217

Funding

Korea Health Industry Development Institute HI18C2383Korean Society of Neurogastroenterology and Motility KSNM-22-03
6 · The paper itself

Abstract

purposeEndoscopically identifying eosinophilic esophagitis (EoE) is difficult due to its rare incidence and subtle morphology. We aimed to develop a robust and accurate convolutional neural network (CNN) model for EoE identification and classification in endoscopic images. MATERIALS AND

methodsWe collected 548 endoscopic images from 81 patients with EoE and 297 images from 37 normal patients. These datasets were labeled according to the four eosinophilic esophagitis endoscopic reference score (EREFS) features: edema, rings, exudates, and furrows. A multi-task U-Net with an auxiliary classifier on various levels of skip connections (

resultsOur

conclusionOur method showed robust performance compared to expert endoscopists and could assist endoscopists of all experience levels in the early detection of EoE-a rare but clinically important condition.

Indexed as

Eosinophilic EsophagitisEsophagoscopyAdultConvolutional Neural NetworksFemaleHumansMaleNeural Networks, ComputerPilot ProjectsROC CurvediagnosisendoscopyEosinophilic esophagitis

Identifiers

PMID41560382
PMCPMC12834612

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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.