Heart Attack Prediction with Artificial Neural Network

Abstract

According to the American Heart Association, “between 2013 and 2016, 121.5 million American adults had some form of cardiovascular disease.”[1] One of the major factors is that doctors may misdiagnose the patients with heart attack and fail to prevent the progressive illness from worsening in the early stage. In this paper, we construct and evaluate an efficient artificial neural network model for analyzing patients’ feature data and predicting the probability of a patient to get a heart attack. With the help of our heart attack prediction model, doctors are able to discover the heart attack early. They can also prescribe medicine for the heart attack patients accurately with the aid of the feature analyzation function of our model. Our heart attack prediction model reaches a high accuracy of 88.51%, which is better than other models.