Automatic evaluation of atlantoaxial subluxation in rheumatoid arthritis by a deep learning model.

Journal: Arthritis research & therapy
Published Date: Sep 25, 2023

Abstract

BACKGROUND: This work aims to develop a deep learning model, assessing atlantoaxial subluxation (AAS) in rheumatoid arthritis (RA), which can often be ambiguous in clinical practice.

Authors

  • Yasutaka Okita
    Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka, 565-0871, Japan. y.okita@imed3.med.osaka-u.ac.jp.
  • Toru Hirano
    Department of Rheumatology, Nishinomiya Municipal Central Hospital, Hyogo, Japan.
  • Bowen Wang
    School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Yuta Nakashima
    Osaka University Institute for Datability Science (IDS), Suita, Osaka, Japan.
  • Saki Minoda
    Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka, 565-0871, Japan.
  • Hajime Nagahara
    Institute for Datability Science, Osaka University, Suita, Osaka, Japan.
  • Atsushi Kumanogoh
    Department of Respiratory Medicine, Allergy and Rheumatic Disease, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.

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