This observational study aims to assess the performance of the software called ausculto™. ausculto™ is a collection of computer algorithms that intend to analyse heart sounds recorded from the built-in microphone of a smartphone for abnormal sounds. Participants will have their heart sounds recorded during their normal attendance at the hospitals after consenting to participate in this study. Researchers will manually annotate the recorded heart sounds to create a database for use in future training and testing of artificial intelligence (AI) intended for medical uses.
Study Type
OBSERVATIONAL
Enrollment
220
Collection of lightweight computer algorithms called ausculto™ that is designed to perform real-time heart sound analysis to detect heart murmur.
Queen Mary Hospital
Hong Kong, Hong Kong
Hong Kong Children's Hospital
Kowloon Bay, Hong Kong
Differentiation of Murmurs Associated with Congenital Heart Disease from Normal Heart Sounds and Innocent Murmurs in Heart Sound Recordings
Identification of murmurs associated with congenital heart disease from normal heart sounds and innocent murmurs in recorded heart sounds (phonocardiogram \[PCG\]), measured in the form of sensitivity and specificity.
Time frame: Day 0
Differentiation of Murmurs Associated with Congenital Heart Disease from Normal Heart Sounds and Innocent Murmurs in Heart Sound Recordings
Identification of murmurs associated with congenital heart disease from normal heart sounds and innocent murmurs in recorded heart sounds (phonocardiogram \[PCG\]), measured in the form of positive and negative predictive value and accuracy.
Time frame: Day 0
Number of Adverse Events Reported by Participants or Child Participants' Parent/Legal Guardian During and at the End of Heart Sound Recording That are Determined to be Caused by This Study
Time frame: Day 0
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