Explainable Deep Neural Network for Identifying Cardiac Abnormalities Using Class Activation Map

Abstract

In this study, our team "NTU-Accesslab" present a deep convolutional neural network (CNN) approach, called CNN-GAP, for classifying 12-lead ECGs with multilabel cardiac abnormalities. Additionally, Class Activation Mapping (CAM) is employed for further understanding the decision-making process of this black-box model, making the model more explainable.