Artificial intelligence model to identify elderly patients with locomotive syndrome: A cross-section study.

Journal: Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
PMID: 35148912

Abstract

BACKGROUND: Identifying elderly individuals with locomotive syndrome is important to prevent disability in this population. Although screening tools for locomotive syndrome are available, these require time commitment and are limited by an individual's ability to complete questionnaires independently. To improve on this limitation, we developed a screening tool that uses information on the distribution of pressure on the plantar surface of the foot with an artificial intelligence (AI)-based decision system to identify patients with locomotor syndrome. Herein, we describe our AI-based system and evaluate its performance.

Authors

  • Shinji Takahashi
    Department of Orthopaedic Surgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan.
  • Yuta Nonomiya
    Department of Medical Statistics, Graduate School of Medicine, Osaka Metropolitan University, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan.
  • Hidetomi Terai
    Department of Orthopaedic Surgery, Osaka City University Graduate School of Medicine, Osaka, Japan.
  • Masatoshi Hoshino
    Department of Orthopaedic Surgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan. Electronic address: hoshino717@gmail.com.
  • Shoichiro Ohyama
    Department of Orthopaedic Surgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan.
  • Ayumi Shintani
    Department of Medical Statistics, Graduate School of Medicine, Osaka Metropolitan University, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan.
  • Hiroaki Nakamura
    Department of Orthopaedic Surgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan.

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