A Review on Performance Evaluation using Convolutional Neural Network to Predict Cardiac Event

Cardiovascular diseases (CVD) may cause fatal medical conditions such as brain damage or stroke or even sudden cardiac death. These days, artificial intelligence based on machine learning and deep learning models are being commonly utilized to analyze and classify cardiac disease. Deep learning models have shown a promising performance in the healthcare field. These models have the potential to select high level features from the input data with the help of several hidden layers. Among the deep learning models, Convolutional neural networks (CNNs) are commonly used to process clinical images. This review is concentrated on exploring recent works for analyzing ECGs using CNN. The aim of this research is to investigate whether utilizing CNN provides better results and if patients can be diagnosed earlier before getting cardiac events