B. B. Bin Sheeha

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.