Feasibility of detecting aortic stenosis with mobile phone auscultation data: a pilot study
This study established the feasibility of two innovative approaches, by combining the sound recordings collected from unmodified mobile phones with analysis via nonlinear dynamics software. This work has the potential to improve valvular heart disease detection by overcoming barriers that remain for current standards of care and emerging artificial intelligence solutions.
Authors
- Ryan Close (ORCID: https://orcid.org/0000-0002-3836-485X)
- Kailey J. Kowalski
- Gregory Judson
- Marco Diaz
- Destiny Martinez
- Jacob Zhang
- Martin Huecker
Institutions
- Tufts University (US)
- University of Louisville (US)
- American Society of Echocardiography (US)
- MaineHealth (US)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2026-03-04
- DOI
- https://doi.org/10.3389/fcvm.2026.1768473
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00