Health AI Central
Share:
Peer-Reviewed Publication
J Am Heart Assoc2025;14(3):e036882.February 4, 2025Journal Article

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

Ling Guo1, Nivedita Khobragade1, Spencer Kieu1, Suleman Ilyas2, Preston N Nicely2, Emmanuel K Asiedu2, Fabio V Lima2,3,4, Caroline Currie1, Emileigh Lastowski1, Gaurav Choudhary2,3,5
1Eko Health Inc. Emeryville CA USA.
2Warren Alpert Medical School Brown University Providence RI USA.
3Brown University Helath Cardiovascular Institute Providence RI USA.
4University of California, San Francisco, Heart & Vascular San Francisco CA USA.
5VA Providence Healthcare System Providence RI USA.
PubMed PMC DOI PDF

Abstract

BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion and screening tools not being easily accessible such as echocardiography. A new readily available screening tool to identify elevated pulmonary artery systolic pressures is needed to help with the prognosis and timely treatment of underlying causes suc…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.