Prediction of Cardiovascular Disease Using Machine Learning Techniques

Abstract: The medical and health-care industries gather vast volumes of data that could include some secret knowledge that can help make better decisions. Advanced data mining methods are used to provide appropriate results and make successful data decisions. A neural network is used in an efficient cardiovascular disease prediction method to predict the risk level of heart disease. For prediction, the device uses a variety of medical parameters such as age, sex, blood pressure, cholesterol, and obesity. The cardiovascular disease prediction method forecasts the risk of heart disease in patients. Relationships between people are an example of significant understanding. It allows medical causes and trends linked to heart disease to be identified. As a training algorithm, we used a multilayer perceptron neural network with back propagation. The obtained results show that the designed diagnostic device is capable of accurately predicting the risk of heart disease.

Keywords: Genetic Algorithm, Data mining, Naive Bayes, Multilayer perceptron neural network, Machine Learning, Deep Learning, Neural network.