Evaluation of the DAMSUN-HF trial: the role of an artificial intelligence stethoscope in detecting reduced ejection fraction in patients living in a low-resource region

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Authors: D. Abramov, Baljash S. Cheema, Kalliopi Keramida, Kaveh Hosseini, Marat Fudim, Abdul Mannan Khan Minhas
Cited by: 1
References: 9

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.

Fields of Study & Subjects

Heart Failure Treatment and Management Cardiovascular Function and Risk Factors Phonocardiography and Auscultation Techniques

Publication details

Journal / source
Heart Failure Reviews
Publisher
Springer Science and Business Media LLC
Volume
31
Issue
1
Pages
17–17
Publication date
5 January 2026
Language
EN