Open access
Aug 2026
An empirical comparison of deep CNN architectures for heart sound classification from phonocardiogram signals
This work compares five deep convolutional neural networks, namely LeNet5, AlexNet, VGG16, ResNet-50 and a hybrid LSTM-CNN and a hybrid LSTM-CNN, on the task of separating normal from abnormal heart sounds, and reports accuracy, AUC, sensitivity, specificity, F1 score and the Matthews correlation coefficient.
A. Al Tawil, B. B. Bin Sheeha, Aseel Aburub
· Frontiers in Physiology · 0 citations