About this trial
The goal of this observational study is to evaluate accuracy of portable electronic stethoscope and machine learning-based diagnostic algorithms for detecting the disease in people with valvular heart disease and healthy controls. The main question it aims to answer is:
Is portable electronic stethoscope and machine learning-based diagnostic algorithms allow accurate detection of valvular heart disease?
Researchers will compare diagnostic algorithm's predictions with the clinicians' predictions to see if the diagnostic results are accurate.
Participants will
* take echocardiogram * take electrocardiogram using BPM Core * get the heart auscultation data measured via electronic stethoscope
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Voluntarily agrees to participate by proving written informed consent
Have echocardiography done within 5 years
Disqualifiers
Mechanical heart valve
Adult congenital heart disease
Trial population
25 with aortic stenosis, 25 with mitral stenosis, 25 with mitral regurgitation, 25 with tricuspid regurgitation, and 25 without valvular heart disease
Trial design
Case-control
Prospective
Treatments tested in this trial
BPM Core
DeviceHeart auscultation data will be collected from the patients in 5 different groups using BPM Core
Treatment groups
Trial outcomes
Primary outcomes
Accuracy of valvular heart disease diagnosis using portable electronic stethoscope and machine learning-based diagnostic algorithms.
Comparison between the algorithm diagnosis to those made by the clinicians using the collected heart auscultation data and echocardiogram results
Sponsors and contacts
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