Machine learning models with time-series clinical features to predict radiographic progression in patients with ankylosing spondylitis.

Journal: Journal of rheumatic diseases
Published Date: Dec 20, 2023

Abstract

OBJECTIVE: Ankylosing spondylitis (AS) is chronic inflammatory arthritis causing structural damage and radiographic progression to the spine due to repeated and continuous inflammation over a long period. This study establishes the application of machine learning models to predict radiographic progression in AS patients using time-series data from electronic medical records (EMRs).

Authors

  • Bon San Koo
    Department of Internal Medicine, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Seoul, Korea.
  • Miso Jang
    Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Ji Seon Oh
    Department of Information Medicine, Big Data Research Center, Asan Medical Center, Seoul, Korea.
  • Keewon Shin
    Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Seunghun Lee
    Department of Radiology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea.
  • Kyung Bin Joo
    Department of Radiology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea.
  • Namkug Kim
    Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Tae-Hwan Kim
    Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea.

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