Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform

Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform

Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinically significant information. The objective of this...

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Bibliographic Details
Main Authors: John S. Chorba, Avi M. Shapiro, Le Le, John Maidens, John Prince, Steve Pham, Mia M. Kanzawa, Daniel N. Barbosa, Caroline Currie, Catherine Brooks, Brent E. White, Anna Huskin, Jason Paek, Jack Geocaris, Dinatu Elnathan, Ria Ronquillo, Roy Kim, Zenith H. Alam, Vaikom S. Mahadevan, Sophie G. Fuller, Grant W. Stalker, Sara A. Bravo, Dina Jean, John J. Lee, Medeona Gjergjindreaj, Christos G. Mihos, Steven T. Forman, Subramaniam Venkatraman, Patrick M. McCarthy, James D. Thomas
Format: Article
Language:English
Published: Wiley 2021-05-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
auscultation
machine learning
neural networks
physical examination
valvular heart disease
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.120.019905

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.120.019905

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