Evidence map›Paper›PMID 42196836›Full record

ArticleDiagnostics (Basel, Switzerland)2026

Deep Learning-Based Diagnosis of Epithelial Ovarian Cancer from Whole-Slide Histopathology Images.

Jihyun Chun, Haeyoun Kang, Heewon Chung, Jae-Myung Jang, Jangwon Seo, Taegyu Kim, Woohyun Lee, Cheolhong Park, Mingi Hong, Han-Mac Brian Kim and 5 more

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

15 authors.

Jihyun ChunDepartment of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Haeyoun KangDepartment of Pathology, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam 13496, Republic of Korea.ORCID 0000-0002-8980-7702
Heewon ChungAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Jae-Myung JangAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Jangwon SeoAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Taegyu KimAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Woohyun LeeAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Cheolhong ParkAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Mingi HongAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Han-Mac Brian KimAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Messi H J LeeAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.ORCID 0000-0003-3096-1112
Kyongseok JangAI Healthcare Innovation Team, MTS Company Inc., Seoul 06178, Republic of Korea.
Chan Kwon JungDepartment of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.ORCID 0000-0001-6843-3708
Sang Wun KimDepartment of Obstetrics and Gynecology, Institute of Women's Life Medical Science, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.ORCID 0000-0002-8342-8701
Ahwon LeeDepartment of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.ORCID 0000-0002-2523-9531

Funding

Ministry of Health and Welfare RS-2021-KH113146National Cancer Center RS-2023-CC138464
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

computational pathologycomputer-assisted diagnosisdeep learningdigital pathologyovary

Identifiers

PMID42196836
PMCPMC13206691

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.