CHSD-Net: Children Heart Sound Abnormality Detection Network

A stethoscope is commonly used to check the heart health of infants by measuring heart movement through sound. However, diagnosis using this equipment heavily relies on the clinician’s expertise and experience, which can result in missed early detection in cases with minimal symptoms. This study aimed to propose and verify a deep learning model that can diagnose congenital heart disease early from time series data of the heart’s audio type, which could be measured with a stethoscope. The proposed architecture is a hybrid combined model of CNN and LSTM, which involves combining 2D-CNN with LSTM layers confirmed that early detection was possible with a high accuracy of 97.8%.