Computer Engineering Commons^™

Detection Of Myocardial Infarction Using Ecg And Multi-Scale Feature Concatenate, Jia-Zheng Jian, Tzong-Rong Ger, Han-Hua Lai, Chi-Ming Ku, Chiung-An Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Diverse computer-aided diagnosis systems based on convolutional neural networks were applied to automate the detection of myocardial infarction (MI) found in electrocardiogram (ECG) for early diagnosis and prevention. However; issues; particularly overfitting and underfitting; were not being taken into account. In other words; it is unclear whether the network structure is too simple or complex. Toward this end; the proposed models were developed by starting with the simplest structure: a multi-lead features-concatenate narrow network (N-Net) in which only two convolutional layers were included in each lead branch. Additionally; multi-scale features-concatenate networks (MSN-Net) were also implemented where larger features were being …