Application of Machine Learning to Osteoporosis and Osteopenia Screening Using Hand Radiographs.

Journal: The Journal of hand surgery
PMID: 39556066

Abstract

PURPOSE: Fragility fractures associated with osteoporosis and osteopenia are a common cause of morbidity and mortality. Current methods of diagnosing low bone mineral density require specialized dual x-ray absorptiometry (DXA) scans. Plain hand radiographs may have utility as an alternative screening tool, although optimal diagnostic radiographic parameters are unknown, and measurement is prone to human error. The aim of the present study was to develop and validate an artificial intelligence algorithm to screen for osteoporosis and osteopenia using standard hand radiographs.

Authors

  • Anna Luan
    From the Division of Plastic Surgery, Department of Surgery.
  • Zeshaan Maan
    Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA.
  • Kun-Yi Lin
    Department of Orthopedics, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China.
  • Jeffrey Yao
    Department of Orthopaedic Surgery, Stanford University School of Medicine, Stanford, CA; Robert A. Chase Hand and Upper Limb Center, Department of Orthopaedic Surgery, Stanford University Medical Center, Redwood City, CA. Electronic address: jyao@stanford.edu.

Keywords

External Resources

Popular Topics
Recent Journals