Evidence map›Paper›PMID 41008694›Full record

ArticleDiagnostics (Basel, Switzerland)2025

Automated Computer-Assisted Diagnosis of Pleural Effusion in Chest X-Rays via Deep Learning.

Ya-Yun Huang, Yu-Ching Lin, Sung-Hsin Tsai, Tsun-Kuang Chi, Tsung-Yi Chen, Shih-Wei Chung, Kuo-Chen Li, Wei-Chen Tu, Patricia Angela R Abu, Chih-Cheng Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Observational
  2. 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.

Ya-Yun HuangProgram on Semiconductor Manufacturing Technology Academy of Innovative Semiconductor and Sustainable Manufacturing, National Cheng Kung University, Tainan City 701401, Taiwan.ORCID 0009-0009-0505-3375
Yu-Ching LinDepartment of Medicine, College of Medicine, Chang Gung University, Taoyuan City 333423, Taiwan.ORCID 0000-0002-0702-5169
Sung-Hsin TsaiDepartment of Medical Education, Chang Gung Memorial Hospital Linkou, Taoyuan City 333423, Taiwan.
Tsun-Kuang ChiDepartment of Electrical Engineering, Ming Chi University of Technology, New Taipei City 243303, Taiwan.ORCID 0009-0003-7109-6492
Tsung-Yi ChenDepartment of Electronic Engineering, Feng Chia University, Taichung City 40724, Taiwan.ORCID 0009-0003-5964-6084
Shih-Wei ChungDepartment of Electronic Engineering, Feng Chia University, Taichung City 40724, Taiwan.
Kuo-Chen LiDepartment of Information Management, Chung Yuan Christian University, Taoyuan City 320317, Taiwan.ORCID 0000-0002-0110-5491
Wei-Chen TuProgram on Semiconductor Manufacturing Technology Academy of Innovative Semiconductor and Sustainable Manufacturing, National Cheng Kung University, Tainan City 701401, Taiwan.ORCID 0000-0003-1134-5859
Patricia Angela R AbuAteneo Laboratory for Intelligent Visual Environments, Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City 1108, Philippines.ORCID 0000-0002-8848-6644
Chih-Cheng ChenDepartment of Automatic Control Engineering, Feng Chia University, Taichung City 40724, Taiwan.

Funding

National Science and Technology Council 112-2410-H-197-002-MY2, 113-2314-B-182A-140, 113-2221-E-131-026, 114-2221-E-035-032, 114-2221-E-131-009, and 114-2314-B-182A-051.Research Support of the Feng Chia University Research Program 24H00810
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

chest X-raysdeep learningimage enhancementmedical imagepleural effusion

Identifiers

PMID41008694
PMCPMC12468862

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.