Artificial Intelligence-Enhanced ECG for Predicting Cardiac Magnetic Resonance-Defined Myocardial Injury in Acute Myocardial Infarction: An External Validation Study
This retrospective, single-center external validation study evaluates whether two commercially approved artificial intelligence-enhanced electrocardiography (AI-ECG) algorithms (AiTiA LVSD and AiTiA MI; Medical AI Co., Ltd.), applied to a single pre-percutaneous coronary intervention (PCI) 12-lead ECG, predict cardiac magnetic resonance (CMR)-defined myocardial injury in patients with acute myocardial infarction (AMI). The primary endpoint is a large infarct (late gadolinium enhancement >17.9% of left ventricular mass); secondary endpoints are CMR left ventricular ejection fraction (LVEF) ≤40% and microvascular obstruction (MVO).
Acute Myocardial Infarction Prediction Using Artificial Intelligence Applied to Electrocardiogram Images
ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) Trial
AI-Powered ECG Detecting Culprit Vessel Blood Flow Abnormality in ACS
Artificial Intelligence System for Early Warning of Adverse Events in Acute Myocardial Infarction