Evidence map›Paper›PMID 41155770›Full record

ArticleMedicina (Kaunas, Lithuania)2025

Comparison of the Prognostic Performance of Various Machine Learning Models in Patients with Acute Myocardial Infarction: Results from the COREA-AMI Registry.

Ji-Hoon Jung, Kyusup Lee, Kiyuk Chang, Youngkeun Ahn, Sung-Ho Her, Sangin Lee

Abstract readMulticenter Study
In one paragraph

Article in Medicina (Kaunas, Lithuania), 2025. 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

6 authors.

Ji-Hoon JungDepartment of Information and Statistics, Chungnam National University, Daejeon 34134, Republic of Korea.ORCID 0000-0002-5994-5434
Kyusup LeeDepartment of Cardiology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 34943, Republic of Korea.ORCID 0000-0003-0149-5503
Kiyuk ChangDepartment of Cardiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Youngkeun AhnDepartment of Cardiology, Chonnam National University Hospital, Gwangju 61469, Republic of Korea.
Sung-Ho HerDepartment of Cardiology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul 16247, Republic of Korea.ORCID 0000-0002-1548-4154
Sangin LeeDepartment of Information and Statistics, Chungnam National University, Daejeon 34134, Republic of Korea.ORCID 0000-0001-8367-7954

Funding

National Research Foundation of Korea RS-2022-NR068754
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Machine LearningMyocardial InfarctionAgedFemaleHumansLogistic ModelsMaleMiddle AgedPercutaneous Coronary InterventionPrognosisRegistriesRisk AssessmentRisk Factorsacute myocardial infarctionmachine learningpredictorsprognosisrandom forest

Identifiers

PMID41155770
PMCPMC12566565

What OpenQuestion holds

Textmetadata
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.