Back to Search
Journal ArticleOpen Access

Coronary Artery Heart Disease Prediction: A Comparative Study of Computational Intelligence Techniques

Author Affiliations
Khulna University of Engineering and Technology, Central Queensland University
Published InIETE Journal of Research
Year2020
Citations256

Abstract

Diseases is an unusual circumstance that affects single or more parts of a human’s body. Because of lifestyle and patrimonial, different kinds of disease are increasing day by day. Among all those diseases, heart disease turns out to be the most common disease and the impact of this ailment is dangerous than all other diseases. In this paper, we compared a number of computational intelligence techniques for the prediction of coronary artery heart disease. Seven computational intelligence techniques named as Logistic Regression (LR), Support Vector Machine (SVM), Deep Neural Network (DNN), Decision Tree (DT), Naïve Bayes (NB), Random Forest (RF), and K-Nearest Neighbor (K-NN) were applied and a comparative study was drawn. The performance of each technique was evaluated using…
View at Publisher

BORR does not host full-text PDFs. The button above takes you to the original publisher.