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

A. Maruthamuthu, Murugesan Punniyamoorthy, Swetha Manasa Paluru and Sindhura Tammuluri

International Journal of Enterprise Network Management, 2019, vol. 10, issue 2, 109-117

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. (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijenma:v:10:y:2019:i:2:p:109-117

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