Heart disease classification based on ECG using machine learning models

One of the most critical steps when diagnosing cardiovascular disorders is examining and processing ECG data. Classification of health and ill persons is the primary focus of research in this Area, and approaches based on machine learning are being used more often. Research in this Area focuses mainly on classification, and an increasing number of researchers are turning to techniques based on machine learning. In this particular investigation, the methods of Gaussian NB, Random Forest, Logistic Regression, Linear Discriminant Analysis, and Dummy Classifier were used for the automated categorization of Electrocardiography (ECG) data.