Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.

Journal: Yonsei medical journal
Published Date: Feb 1, 2019

Abstract

PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, these predictive models have several limitations, such as user convenience and reproducibility. The purpose of this study was to develop a T2DM predictive model using electronic medical records (EMRs) and machine learning and to compare the performance of this model with traditional statistical methods.

Authors

  • Byoung Geol Choi
    Research Institute of Health Sciences, Korea University College of Health Science, Seoul, Korea.
  • Seung Woon Rha
    Cardiovascular Center, Korea University Guro Hospital, Seoul, Korea. swrha617@yahoo.co.kr.
  • Suhng Wook Kim
    Research Institute of Health Sciences, Korea University College of Health Science, Seoul, Korea.
  • Jun Hyuk Kang
    Center for Gastric Cancer, National Cancer Center, Goyang, Korea.
  • Ji Young Park
    Division of Gastroenterology, Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea.
  • Yung Kyun Noh
    School of Mechanical & Aerospace Engineering, Seoul National University, Seoul, Korea. nohyung@snu.ac.kr.

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