health life sciences medicine
Congenital heart diseases affect about 1% of newborns, representing an important morbidity and mortality factor for several severe conditions, including advanced heart failure [1]. In a 2019 survey, it was estimated that congenital heart diseases affect over 500,000 children in East Africa [2], and about 8 in every 1000 live births [3]. Acquired heart diseases include rheumatic fever and the Kawasaki disease, the former being a serious public health problem in developing regions, e.g., rural Brazil [4]. Several regions of developing countries have difficulties in diagnosing and treating both congenital and acquired heart conditions in children. This is mainly due to the lack of infrastructure and cardiology specialists in geographically large areas and difficulty in accessing health services. In addition, the current COVID-19 pandemic poses new difficulties in the clinical evaluation of patients by delaying important in-person patient-doctor contacts, negatively impacting screening and monitoring activities. A non-invasive assessment of the mechanical function of the heart, performed at point-of-care settings, can provide early information regarding congenital and acquired heart diseases in children. The lack of early diagnoses of these conditions represents a major public health problem, especially in underprivileged countries with high birth rates [5, 6, 7]. In particular, cardiac auscultation and the analysis of the phonocardiogram (PCG) can unveil fundamental clinical information regarding heart malfunctioning caused by congenital and acquired heart disease in pediatric populations. This is achieved by detecting abnormal sound waves, or heart murmurs, in the PCG signal. Murmurs are abnormal waves generated by turbulent blood flow in cardiac and vascular structures. They are closely associated with specific diseases such as septal defects, failure of ductus arteriosus closure in newborns, and defective cardiac valves. Succedent the 2016 Challenge, which focused on classifying normal vs. abnormal heart sounds from a single short recording from a single precordial location [8, 9], this year’s Challenge is devoted to detecting the presence or absence of murmurs from multiple heart sound recordings from multiple auscultation locations, as well as detecting the clinical outcomes.
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https://doi.org/10.13026/t49p-5v35
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Heart Murmur Detection from Phonocardiogram Recordings: The George B. Moody PhysioNet Challenge 2022 was accessed on DATE from https://registry.opendata.aws/challenge-2022.
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