Machine learning to predict incident radiographic knee osteoarthritis over 8 Years using combined MR imaging features, demographics, and clinical factors: data from the Osteoarthritis Initiative.

Journal: Osteoarthritis and cartilage
Published Date: Nov 18, 2021

Abstract

OBJECTIVE: To develop a machine learning-based prediction model for incident radiographic osteoarthritis (OA) of the knee over 8 years using MRI-based cartilage biochemical composition and knee joint structure, demographics, and clinical predictors including muscle strength and symptoms.

Authors

  • G B Joseph
    Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA. Electronic address: gabby.joseph@ucsf.edu.
  • C E McCulloch
    Department of Epidemiology and Biostatistics, University of California, San Francisco, USA.
  • M C Nevitt
    Department of Epidemiology and Biostatistics, University of California, San Francisco, USA.
  • T M Link
    Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA. Electronic address: Thomas.Link@ucsf.edu.
  • J H Sohn
    Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA.

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