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
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.
Authors
- Kaveh Hosseini (ORCID: https://orcid.org/0000-0001-5676-3099)
- Baljash Cheema (ORCID: https://orcid.org/0000-0002-4105-0579)
- KALLIOPI KERAMIDA
- D. Abramov
- Abdul Mannan Khan Minhas (ORCID: https://orcid.org/0000-0002-9829-3520)
- Marat Fudim
Institutions
- Northwestern University (US)
- University of Copenhagen (DK)
- Baylor College of Medicine (US)
- National and Kapodistrian University of Athens (GR)
- Loma Linda University (US)
- Gentofte Hospital (DK)
- Clinical Research Institute (US)
- Loma Linda University Health Care (US)
- St Savas Hospital (GR)
- Duke Medical Center (US)
- Northwestern Medicine (US)
Publication Details
- Journal
- Heart Failure Reviews
- Published
- 2026-01-05
- DOI
- https://doi.org/10.1007/s10741-025-10591-2
- Primary Topic
- Heart Failure Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00