Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques.

Journal: Preventing chronic disease
PMID: 31538566

Abstract

INTRODUCTION: As one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive models to identify risk factors for type 2 diabetes, which could help facilitate early diagnosis and intervention and also reduce medical costs.

Authors

  • Zidian Xie
    Clinical and Translational Science Institute, University of Rochester School of Medicine and Dentistry, 265 Crittenden Blvd CU 420708, Rochester, NY 14642-0708. Email: zidian_xie@urmc.rochester.edu.
  • Olga Nikolayeva
    Goergen Institute of Data Sciences, University of Rochester, Rochester, New York.
  • Jiebo Luo
  • Dongmei Li
    Clinical and Translational Science Institute, University of Rochester School of Medicine and Dentistry, Rochester, New York.

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