Heart Murmur Detection from Phonocardiogram Recordings: The George B. Moody PhysioNet Challenge 2022
Objective Cardiac auscultation is an accessible diagnostic screening tool that can help to identify patients with heart murmurs for follow-up diagnostic screening and treatment, especially in resource-constrained environments. However, experts are needed to interpret the heart sound recordings, limiting the accessibility of auscultation for cardiac care. The George B. Moody PhysioNet Challenge 2022 invites teams to develop automated approaches for detecting abnormal heart function from multi-location phonocardiogram (PCG) recordings of heart sounds. Approach For the Challenge, we sourced 5272 PCG recordings from 1568 pediatric patients in rural Brazil. We required the Challenge participants to submit the complete code for training and running their models, improving the transparency, reproducibility, and utility of the diagnostic algorithms. We devised a cost-based evaluation metric that captures the costs of screening, treatment, and diagnostic errors, allowing us to investigate the benefits of algorithmic pre-screening and facilitate the development of more clinically relevant algorithms. Main results So far, over 80 teams have submitted over 600 algorithms during the course of the Challenge, representing a diversity of approaches in academia and industry. We will update this manuscript to share an analysis of the Challenge after the end of the Challenge. Significance The use of heart sound recordings for both heart murmur detection and clinical outcome identification allowed us to explore the potential of automated approaches to provide accessible pre-screening of less-resourced populations. The submission of working, open-source algorithms and the use of novel evaluation metrics supported the reproducibility, generalizability, and relevance of the researched conducted during the Challenge.
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