Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation.

Journal: Journal of medical Internet research
Published Date: Jan 13, 2023

Abstract

BACKGROUND: Osteoporosis is one of the diseases that requires early screening and detection for its management. Common clinical tools and machine-learning (ML) models for screening osteoporosis have been developed, but they show limitations such as low accuracy. Moreover, these methods are confined to limited risk factors and lack individualized explanation.

Authors

  • Bogyeong Suh
    School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.
  • Heejin Yu
    School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.
  • Hyeyeon Kim
    Department of Family Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea.
  • Sanghwa Lee
    Biomedical Engineering Research Center, Asan Medical Center, Seoul 05505, Republic of Korea.
  • Sunghye Kong
    Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Jin-Woo Kim
    Department of Orthopaedic Surgery, Nowon Eulji Medical Center, Seoul, South Korea.
  • Jongeun Choi
    MSU Center for Orthopedic Research, Michigan State University, Lansing, MI, USA; School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea.

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