A deep learning method for predicting knee osteoarthritis radiographic progression from MRI.

Journal: Arthritis research & therapy
Published Date: Oct 18, 2021

Abstract

BACKGROUND: The identification of patients with knee osteoarthritis (OA) likely to progress rapidly in terms of structure is critical to facilitate the development of disease-modifying drugs.

Authors

  • Jean-Baptiste Schiratti
    Owkin Lab, Owkin, Inc, New York, NY, USA.
  • Remy Dubois
    Owkin Lab, Owkin, Inc, New York, NY, USA.
  • Paul Herent
    Owkin Lab, Owkin, Inc, New York, NY, USA.
  • David Cahané
    Owkin, 12 Rue Martel, 75010, Paris, France.
  • Jocelyn Dachary
    Owkin Lab, Owkin, Inc, New York, NY, USA.
  • Thomas Clozel
    OWKIN Paris, France.
  • Gilles Wainrib
    Ecole Normale Supérieure, Département d'Informatique, équipe DATA, Paris, France.
  • Florence Keime-Guibert
    Servier, Research and Development, 50 rue Carnot, 92284, Suresnes Cedex, France.
  • Agnes Lalande
    Servier, Research and Development, 50 rue Carnot, 92284, Suresnes Cedex, France.
  • Maria Pueyo
    Servier, Research and Development, 50 rue Carnot, 92284, Suresnes Cedex, France.
  • Romain Guillier
    Servier, Research and Development, 50 rue Carnot, 92284, Suresnes Cedex, France.
  • Christine Gabarroca
    Servier, Research and Development, 50 rue Carnot, 92284, Suresnes Cedex, France.
  • Philippe Moingeon
    Servier, Research and Development, 50 rue Carnot, 92284 Suresnes Cedex, France. Electronic address: philippe.moingeon@servier.com.

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