Predicting Occlusion Myocardial Infarctions in the Emergency Department Using Artificial Intelligence.

ABSTRACT:

Objectives

The objective was to develop an artificial intelligence (AI) model for predicting acute coronary occlusion myocardial infarction (OMI) in patients with chest pain at the emergency department (ED), using information that is widely available early in the ED assessment.

Methods

In a cohort of 24,511 consecutive adult ED patients with chest pain from 5 Swedish hospitals, OMI cases were identified through register data and manual review of health records and angiographies. Ambulance patients bypassing the ED due to ST-elevation myocardial infarction (STEMI) were not included in the cohort. A deep-learning AI model was created to predict OMI using the electrocardiogram, optionally combined with other early ED data, including medical history and initial lab values. The m

SUBMITTER: Nystrom A 

PROVIDER: S-EPMC12818230 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature