Deep learning approach to predict pain progression in knee osteoarthritis.

Journal: Skeletal radiology
Published Date: Apr 9, 2021

Abstract

OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting pain progression in subjects with or at risk of knee osteoarthritis (OA).

Authors

  • Bochen Guan
    Department of Radiology, University of Wisconsin, 1111 Highland Avenue, Madison, WI, 53705-2275, USA. bochen.guan@gmail.com.
  • Fang Liu
    The First Clinical Medical College of Gannan Medical University, Ganzhou 341000, Jiangxi Province, China.
  • Arya Haj Mizaian
    Department of Radiology, Johns Hopkins University, Baltimore, MD, USA.
  • Shadpour Demehri
    Department of Radiology, The Johns Hopkins Hospital, Baltimore, MD 21287.
  • Alexey Samsonov
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Ali Guermazi
    Department of Radiology, Boston University School of Medicine, Boston, MA, 02118, USA.
  • Richard Kijowski
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

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