Development and Evaluation of a Deep Learning–Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope
We demonstrated the feasibility of using digital stethoscopes in conjunction with deep learning algorithms as a low-cost, noninvasive, and easily accessible screening tool for early detection of pulmonary hypertension.
Authors
- Gaurav Choudhary (ORCID: https://orcid.org/0000-0001-9343-5481)
- Emileigh Lastowski
- Caroline Currie (ORCID: https://orcid.org/0009-0002-3867-9592)
- Suleman Ilyas (ORCID: https://orcid.org/0000-0002-0800-8299)
- Preston N. Nicely (ORCID: https://orcid.org/0000-0002-0374-6612)
- Ling Guo (ORCID: https://orcid.org/0000-0001-8394-4338)
- Nivedita Khobragade (ORCID: https://orcid.org/0000-0001-9736-043X)
- Emmanuel K. Asiedu
- Fabio V. Lima (ORCID: https://orcid.org/0000-0001-8408-6902)
- Spencer Kieu
Institutions
- University of California, San Francisco (US)
- Brown University (US)
- Providence VA Medical Center (US)
Publication Details
- Journal
- Journal of the American Heart Association
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1161/jaha.124.036882
- Citations
- 6
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 9.11