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.

Inclusion Criteria:

• 18+ years old
• Patient or patient's legal healthcare proxy consents to participation
• Documented history of SHD
• Undergoing (or has undergone, within 30 days) a complete echocardiogram
• Willing to have heart recordings done with two different electronic stethoscopes

Exclusion Criteria:

• Patient or proxy is unwilling/unable to give written informed consent
• Unable to complete a complete echocardiogram, or none recent completed within the last 30 days
• No documented history of SHD
• Experiencing a known or suspected acute cardiac event
• Mechanical ventricular support (such as ECMO, LVAD, RVAD, BiVAD, Impella, intra-aortic balloon pumps, TAH, VentrAssist, DuraHeart, HVAD, EVAHEART LVAS, HeartMate, Jarvik 2000)
• Unwilling or unable to follow or complete study procedures

Potential research subjects will be screened for eligibility from cardiology clinics, echocardiogram clinics, and inpatient areas. In order to be eligible, a patient must be 18+ years of age, have a documented history of structural heart disease, and has undergone an echocardiogram within the last 30 days. If a patient meets all of the specified inclusion criteria, and none of the specified exclusion criteria, the patient or their proxy will be approached to discuss participation in the study.