Work

OR2-28 | Diagnostic Accuracy of AI Models, Stemi Criteria, and Clinician Interpretations in Acute Myocardial Infarction: A Meta-Analysis of Pooled AUC Data

Year: 2025

Type: review

Study designs: Systematic Review, Meta-Analysis

Abstract: Early and accurate diagnosis of acute myocardial infarction (AMI) is essential for optimal treatment. This meta-analysis aims to compare the diagnostic performance of artificial intelligence (AI) models, STEMI criteria, and clinicians using pooled area under the curve (AUC) data from several key studies.

Source: Journal of the Society for Cardiovascular Angiography & Interventions

DOI: 10.1016/j.jscai.2025.102698

Authors: Ibrahim Kamel, Ahmed K. Mahmoud, Kareem Mohamed, Ahmed Younes, Benjamin Horn

Institutions: Boston Medical Center, St. Elizabeth's Medical Center, East Carolina University

Language: English

Topic: Acute Myocardial Infarction Research

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,400