Novel artificial intelligence model using electrocardiogram for detecting acute myocardial infarction needing revascularization.

ABSTRACT:

Aims

Rapid myocardial revascularization in patients with acute myocardial infarction (AMI) is essential to improve clinical outcomes. There is still room for improvement in the timely diagnosis of AMI. This study aimed to develop an artificial intelligence (AI) model using electrocardiograms (ECGs) for detecting AMI needing revascularization.

Methods and results

A total of 723 389 ECGs from 300 627 patients in the derivation cohort at a single centre between 2013 and 2020, including 5872 patients with AMI (1.95%) who underwent revascularization, were used for model training and internal testing. A transformer-based deep learning model, initially trained on about one million unlabelled ECGs through self-supervised learning, was fine-tuned for AMI detection. The model's final

SUBMITTER: Cho KH 

PROVIDER: S-EPMC12282381 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature