Clinical Application of a Big Data Machine Learning Analysis Model for Osteoporotic Fracture Risk Assessment Built on Multicenter Clinical Data in Qingdao City.

Journal: Discovery medicine
PMID: 39851223

Abstract

BACKGROUND: Osteoporotic fractures (OPF) pose a public health issue, imposing significant burdens on families and societies worldwide. Currently, there is a lack of comprehensive and validated risk assessment models for OPF. This study aims to develop a model to assess and predict the risk of OPF in Qingdao City, China.

Authors

  • Bing Li
  • Yanru Yang
    Department of Biochemistry and Molecular Biology, School of Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China.
  • Feng Shen
    Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
  • Yuelei Wang
    Department of Spinal Surgery, The Affiliated Hospital of Qingdao University, 266000 Qingdao, Shandong, China.
  • Ting Wang
    CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
  • Xiaxia Chen
    Department of Spinal Surgery, The Affiliated Hospital of Qingdao University, 266000 Qingdao, Shandong, China.
  • Chun Lu
    Science and Education Department, Zibo Orthopedic Hospital, 255040 Zibo, Shandong, China.

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