Osteoporotic fractures prediction in Chinese postmenopausal women: a machine learning-based multi-dimensional approach

), age, albumin-to-globulin ratio, and neutrophil percentage as the most influential predictors, with osteocalcin N-mid fragment contributing more prominently than other BTMs. In conclusion, this machine learning-based model effectively identified key risk factors for osteoporotic fractures in postmenopausal women, and integrating BMD with biochemical and clinical indicators may improve fracture risk prediction and support clinical screening and risk stratification.

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Publication Details

Journal
Frontiers in Endocrinology
Published
2026-04-17
DOI
https://doi.org/10.3389/fendo.2026.1788788
Primary Topic
Bone health and osteoporosis research
Type
article
Field-Weighted Citation Impact
0.00

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article

Osteoporotic fractures prediction in Chinese postmenopausal women: a machine learning-based multi-dimensional approach

Longwang Tan, Chi Zhang, Yang Guo, Chuang Liu et al.
Frontiers in Endocrinology
Bone health and osteoporosis research
article

Osteoporotic fractures prediction in Chinese postmenopausal women: a machine learning-based multi-dimensional approach

Longwang Tan, Chi Zhang, Yang Guo, Chuang Liu, Kok-Yong Chin, Wei Zhu, Yongjun Jia, Jiang Shuai
article en

Abstract

), age, albumin-to-globulin ratio, and neutrophil percentage as the most influential predictors, with osteocalcin N-mid fragment contributing more prominently than other BTMs. In conclusion, this machine learning-based model effectively identified key risk factors for osteoporotic fractures in postmenopausal women, and integrating BMD with biochemical and clinical indicators may improve fracture risk prediction and support clinical screening and risk stratification.

Frontiers in EndocrinologyVol. 17
Xizang Minzu University (CN), Morpho (United States) (US), University Kebangsaan Malaysia Medical Centre (MY), Xian Central Hospital (CN), Affiliated Hospital of Shaanxi University of Chinese Medicine (CN), Shaanxi Institute of International Trade & Commerce (CN)
Universiti Kebangsaan Malaysia
Good health and well-being, Gender equality
Openalex Percentile: Top 18%
Bone health and osteoporosis research
DOIOpen Access PDFOpenAlex
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