The main objective of this study is to evaluate a machine learning model's ability to detect murmurs indicative of structural heart disease ("structural murmur") by analyzing phonocardiogram waveforms-and simultaneous electrocardiogram waveforms when available-in multiple auscultatory positions per subject. Diagnosis of structural murmur will be confirmed by gold-standard echocardiography and reviewed by an expert panel of cardiologists.
Study Type
OBSERVATIONAL
Enrollment
125
Use of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to auscultate and record cardiac phonocardiogram and (when available) electrocardiogram waveforms, as well as heart sounds.
Cox Medical Centers
Springfield, Missouri, United States
RECRUITINGPrimary outcome
Evaluate a machine learning model's ability to detect murmurs indicative of structural heart disease ("structural murmur") by analyzing phonocardiogram waveforms-and simultaneous electrocardiogram waveforms when available-in multiple auscultatory positions per subject. Diagnosis of structural murmur will be confirmed by gold-standard echocardiography and review by an expert panel of cardiologists.
Time frame: 6 months
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