Artificial Intelligence in Echocardiography for Acute Coronary Syndromes: Current Evidence and Integration With Electrocardiography and Biomarkers

Abstract

Early diagnosis of acute coronary syndromes (ACS) remains challenging because electrical, mechanical, and biochemical manifestations of myocardial ischemia evolve at different stages of the ischemic cascade. Although electrocardiography (ECG), cardiac biomarkers, and echocardiography are routinely used in clinical practice, these diagnostic modalities are commonly interpreted independently, potentially delaying recognition of myocardial ischemia. Recent advances in artificial intelligence (AI) offer new opportunities to improve diagnostic accuracy through multimodal integration, with echocardiography serving as the central imaging modality.