Evidence map›Paper›PMID 39728285›Full record

ArticleJournal of cardiovascular development and disease2024

Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study.

Liam Butler, Alexander Ivanov, Turgay Celik, Ibrahim Karabayir, Lokesh Chinthala, Mohammad S Tootooni, Byron C Jaeger, Luke T Patterson, Adam J Doerr, David D McManus and 3 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cardiovascular development and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07163767 (Acute Myocardial Infarction Prediction Using Artificial Intelligence Applied to Electrocardiogram Images), which is not on this map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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.

NCT07163767 active not recruitingnot on this mapstarted 2025, after this paper: background citation

Acute Myocardial Infarction Prediction Using Artificial Intelligence Applied to Electrocardiogram Images

TypeobservationalSponsorGuangdong Provincial People's HospitalRan2025 to 2028Enrolled150,000ConditionsAcute Myocardial Infarction (AMI), Electrocardiography, Artifical IntelligenceArmsDeep learning approach of ECG for AMI detection
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  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

13 authors.

Liam ButlerCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
Alexander IvanovCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
Turgay CelikCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.ORCID 0000-0001-8418-0130
Ibrahim KarabayirCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
Lokesh ChinthalaCenter for Biomedical Informatics, University of Tennessee Health Sciences Center, Memphis, TN 38163, USA.ORCID 0000-0002-1258-8353
Mohammad S TootooniHealth Informatics and Data Science, Loyola University Chicago, Maywood, IL 60660, USA.ORCID 0000-0001-7235-4914
Byron C JaegerDivision of Public Health Science, Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
Luke T PattersonCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
Adam J DoerrDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01655, USA.
David D McManusDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01655, USA.
Robert L DavisCenter for Biomedical Informatics, University of Tennessee Health Sciences Center, Memphis, TN 38163, USA.
David HerringtonCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
Oguz AkbilgicCardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.ORCID 0000-0003-0313-9254

Funding

Wake Forest Center for Artificial Intelligence Research 2023-01
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

ECG-AIECG-AI-Coxfatal coronary heart diseaseFCHDrisk predictiontime-dependent risk

Identifiers

PMID39728285
PMCPMC11678222

What OpenQuestion holds

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Registered trials

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.