Comparing the accuracy of four machine learning models in predicting type 2 diabetes onset within the Chinese population: a retrospective study.

Journal: The Journal of international medical research
Published Date:

Abstract

OBJECTIVE: To evaluate the effectiveness of machine learning (ML) models in predicting 5-year type 2 diabetes mellitus (T2DM) risk within the Chinese population by retrospectively analyzing annual health checkup records.

Authors

  • Hongzhou Liu
    Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Song Dong
    Department of Endocrinology, Aerospace Center Hospital, Beijing, China.
  • Hua Yang
  • Linlin Wang
    Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence Application Technology Research Institute, Shenzhen Polytechnic University, Shenzhen, China.
  • Jia Liu
    Department of Colorectal Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, China.
  • Yangfan Du
    Department of Endocrinology, Aerospace Center Hospital, Beijing, China.
  • Jing Liu
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Zhaohui Lyu
    Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Yuhan Wang
    School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
  • Li Jiang
    School of Food Science and Engineering, Hefei University of Technology, Hefei, China.
  • Shasha Yu
  • Xiaomin Fu
    Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.