Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease.

ABSTRACT: Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart disease. Applying machine learning to cardiac auscultation could address this problem, but despite recent interest, few algorithms have been brought to clinical practice. We evaluated a novel suite of Food and Drug Administration-cleared algorithms trained via deep learning on >15 000 heart sound recordings. Methods and Results We validated the algorithms on a data set of 2375 recordings from 615 unique subjects. This data set was collected in real clinical environments using commercially available digital stethoscopes, annotated by board-certified cardiologists, and paired with echocardiograms as the gold standard. To model the algorithm in cli

SUBMITTER: Prince J 

PROVIDER: S-EPMC10757522 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature