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

ABSTRACT: 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 research is to assess the performance of a deep learning algorithm to detect murmurs and clinically significant valvular heart disease using recordings from a commercial digital stethoscope platform. Methods and Results Using >34 hours of previously acquired and annotated heart sound recordings, we trained a deep neural network to detect murmurs. To test the algorithm, we enrolled 962 patients in a clinical study and collected recordings at the 4 primary auscultation locations. Ground truth was

SUBMITTER: Chorba JS 

PROVIDER: S-EPMC8200722 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature