Predictive models for diabetes mellitus using machine learning techniques.

Journal: BMC endocrine disorders
Published Date: Oct 15, 2019

Abstract

BACKGROUND: Diabetes Mellitus is an increasingly prevalent chronic disease characterized by the body's inability to metabolize glucose. The objective of this study was to build an effective predictive model with high sensitivity and selectivity to better identify Canadian patients at risk of having Diabetes Mellitus based on patient demographic data and the laboratory results during their visits to medical facilities.

Authors

  • Hang Lai
    Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada.
  • Huaxiong Huang
    Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada.
  • Karim Keshavjee
    Research Lab for Advanced System Modelling, Ryerson University, Toronto, ON, M5B 2K3, Canada.
  • Aziz Guergachi
    Research Lab for Advanced System Modelling, Ryerson University, Toronto, ON, M5B 2K3, Canada.
  • Xin Gao
    Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.

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