Prediction of subsequent fragility fractures: application of machine learning.

Journal: BMC musculoskeletal disorders
Published Date: Jun 4, 2024

Abstract

BACKGROUND: Machine learning (ML) has shown exceptional promise in various domains of medical research. However, its application in predicting subsequent fragility fractures is still largely unknown. In this study, we aim to evaluate the predictive power of different ML algorithms in this area and identify key features associated with the risk of subsequent fragility fractures in osteoporotic patients.

Authors

  • Mozhdeh Zabihiyeganeh
    Bone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, University of Medical Sciences, Baharestan Sq, Tehran, Iran.
  • Alireza Mirzaei
    Bone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, University of Medical Sciences, Baharestan Sq, Tehran, Iran.
  • Pouria Tabrizian
    Bone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, University of Medical Sciences, Baharestan Sq, Tehran, Iran.
  • Aryan Rezaee
    Bone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, University of Medical Sciences, Baharestan Sq, Tehran, Iran.
  • Abbas Sheikhtaheri
    Health Management and Economics Research Center, Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Islamic Republic of Iran. Electronic address: sheikhtaheri.a@iums.ac.ir.
  • Azade Amini Kadijani
    Bone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, University of Medical Sciences, Baharestan Sq, Tehran, Iran.
  • Bahare Amini Kadijani
    Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
  • Ali Sharifi Kia
    Bone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, University of Medical Sciences, Baharestan Sq, Tehran, Iran. Ashari45@uwo.ca.

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