Paper Title
CNN for Diagnosing Electrocardiogram

Abstract
Recently, artificial intelligence is being used in industries around the world. Among them, the medical and healthcare field is one of the most interesting applications of artificial intelligence with innovative potential, from medical image analysis to electronic health record-based prediction and precision medicine. Clinical healthcare processes are streamlined by a lot of AI technologies. Heart disease ranks high among the causes of death in adults from disease. In Korea, heart disease ranks high among the causes of death for adults from disease. The electrocardiogram test is a test that records and confirms the activity of the heart, which is indicated by heartbeat. This is a basic test to check the health of the heart. It is easy for early detection and early treatment of heart disease. Therefore, this study creates a model for diagnosing electrocardiogram using AI with electrocardiogram data. Therefore, this study creates a model for diagnosing electrocardiogram using AI with electrocardiogram data. Many similar papers have been released, but this paper will analyze the data and compare the accuracy using the CNN neural network structure used in the previous study and the neural network structure we changed. Keywords - Deep learning, Convolutional neural network, Electrocardiogram