A comprehensive approach for osteoporosis detection through chest CT analysis and bone turnover markers: harnessing radiomics and deep learning techniques.

Journal: Frontiers in endocrinology
PMID: 38894742

Abstract

PURPOSE: The main objective of this study is to assess the possibility of using radiomics, deep learning, and transfer learning methods for the analysis of chest CT scans. An additional aim is to combine these techniques with bone turnover markers to identify and screen for osteoporosis in patients.

Authors

  • Kaibin Fang
    Department of Orthopaedic Surgery, The Second Affiliated Hospital of Fujian Medical University, No. 34, Zhongshanbeilu, Quanzhou, 362000, China (K.F., X.L., Z.D.).
  • Xiaoling Zheng
    Liming Vocational University, Quanzhou, 362000, China (X.Z.).
  • Xiaocong Lin
    Department of Orthopaedic Surgery, The Second Affiliated Hospital of Fujian Medical University, No. 34, Zhongshanbeilu, Quanzhou, 362000, China (K.F., X.L., Z.D.).
  • Zhangsheng Dai
    Department of Orthopaedic Surgery, The Second Affiliated Hospital of Fujian Medical University, No. 34, Zhongshanbeilu, Quanzhou, 362000, China (K.F., X.L., Z.D.). Electronic address: daizhangsheng56@fjmu.edu.cn.

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