Abstract
Evaluation of ejection fraction (EF) is paramount for patients with symptoms of heart failure. While transthoracic echocardiography (TTE) is the most common way to evaluate EF, recent advances in artificial intelligence (AI) have opened the door for alternative methods to screen for reduced EF with smaller and more portable technology. The DAMSUN-HF study evaluated the accuracy of an AI-based stethoscope for detecting reduced EF (≤40%) in patients with symptoms of heart failure in a region with geographic and economic barriers to obtaining timely TTE. This mini-review examines the DAMSUN-HF study and highlights the potential clinical implications of the study findings.