Comparing Three Data Mining Algorithms for Identifying the Associated Risk Factors of Type 2 Diabetes.

Journal: Iranian biomedical journal
Published Date: Jan 27, 2018

Abstract

BACKGROUND: Increasing the prevalence of type 2 diabetes has given rise to a global health burden and a concern among health service providers and health administrators. The current study aimed at developing and comparing some statistical models to identify the risk factors associated with type 2 diabetes. In this light, artificial neural network (ANN), support vector machines (SVMs), and multiple logistic regression (MLR) models were applied, using demographic, anthropometric, and biochemical characteristics, on a sample of 9528 individuals from Mashhad City in Iran.

Authors

  • Habibollah Esmaeily
    Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Maryam Tayefi
    Department of Modern Sciences and Technologies, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Majid Ghayour-Mobarhan
    International UNESCO Center for Health Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Alireza Amirabadizadeh
    Medical Toxicology and Drug Abuse Research Center (MTDRC), Birjand University of Medical Sciences, South Khorasan, Iran.

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