PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

Journal: BMC research notes
PMID: 40069865

Abstract

OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bone mineral density (BMD) testing, which has limitations in early detection. This study aims to develop and validate a machine learning approach for osteoporosis identification by integrating demographic data, laboratory and questionnaire data, offering a more practical and effective screening alternative.

Authors

  • Zebing Si
    Department of Sports Medicine, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Speed Capability, The Guangzhou Key Laboratory of Precision Orthopedics and Regenerative Medicine, Jinan University, Guangzhou, 510630, China.
  • Di Zhang
    College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Huajun Wang
    Department of Bone and Joint Surgery, The First Affiliated Hospital of Jinan University.
  • Xiaofei Zheng
    Beijing Institute of Radiation Medicine, Beijing 100850, China.

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