Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis.

Journal: BMC musculoskeletal disorders
PMID: 39633356

Abstract

BACKGROUND: Osteoporosis is one of the most common metabolic diseases that is characterized by a decrease in bone density and a loss of the quality of the bone structure. The use of deep learning in the prediction of osteoporosis can provide a non-invasive, cost-effective, and efficient approach. The aim of this study is to investigate the diagnostic accuracy of deep learning in the prediction of osteoporosis.

Authors

  • Firouz Amani
    Department of Community Medicine, School of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran.
  • Masoud Amanzadeh
    Department of Health Information Management, School of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran. M.amanzadeh@arums.ac.ir.
  • Mahnaz Hamedan
    Ardabil University of Medical Sciences, Ardabil, Iran.
  • Paniz Amani
    Electronic Engineering, Tabriz University, Tabriz, Iran.

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