Cost-effectiveness of opportunistic osteoporosis screening using chest radiographs with deep learning in Germany.

Journal: Aging clinical and experimental research
PMID: 40355760

Abstract

BACKGROUND: Osteoporosis is often underdiagnosed due to limitations in traditional screening methods, leading to missed early intervention opportunities. AI-driven screening using chest radiographs could improve early detection, reduce fracture risk, and improve public health outcomes.

Authors

  • Jean-Yves Reginster
    Research Unit in Public Health, Epidemiology and Health Economics, University of Liege, Belgium; WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Ageing, Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia. Electronic address: jyreginster@uliege.be.
  • Ralf Schmidmaier
    Department of Medicine IV, LMU University Hospital, LMU Munich, Munich, Germany.
  • Majed Alokail
    Protein Research Chair, Biochemistry Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia.
  • Mickaël Hiligsmann
    Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.

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