Title: Prediction of carotid atherosclerosis in patients with impaired glucose tolerance - a performance analysis of machine learning techniques

Authors: A. Maruthamuthu; Murugesan Punniyamoorthy; Swetha Manasa Paluru; Sindhura Tammuluri

Addresses: Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India ' Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India ' Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India ' Department of Management Studies, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India

Abstract: The focus of this paper is to examine factors associated with carotid atherosclerosis in patients with impaired glucose tolerance (IGT), and to predict the rapid progression of carotid intima-media thickness (IMT). The proposed machine learning methods performed well and accurately predicted the progression of carotid IMT. The linear support vector machine, nonlinear support vector machine with a radial basis kernel function, multilayer perceptron (MLP), and the Naive Bayes method were employed. A comparison of these methods was conducted using the Brier score, and the accuracy was tested using a confusion matrix.

Keywords: multilayer perceptron; MLP; support vector machine; SVM; radial basis kernel function; impaired glucose tolerance; IGT; carotid atherosclerosis; Naive Bayesian model; Brier score.

DOI: 10.1504/IJENM.2019.100528

International Journal of Enterprise Network Management, 2019 Vol.10 No.2, pp.109 - 117

Received: 25 Jul 2018
Accepted: 05 Oct 2018
Published online: 29 Jun 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article