The critical role of inflammation in osteoporosis prediction unveiled by a machine learning framework integrating multi-source data
Using inflammation markers and machine learning, we created accurate models to predict osteoporosis. This work confirms inflammation's key role in the disease, providing new insights for early detection and targeted intervention.
Authors
- Hongli Chang (ORCID: https://orcid.org/0000-0002-5371-8855)
- Hongguang Chang
- Peipei Li (ORCID: https://orcid.org/0000-0001-9142-448X)
- Lei Zhu (ORCID: https://orcid.org/0000-0003-1685-7968)
- Wenhao He (ORCID: https://orcid.org/0000-0003-4354-4481)
- Xuenan Wang (ORCID: https://orcid.org/0009-0008-5587-5169)
Institutions
- Fujian Medical University (CN)
- Fujian Provincial Hospital (CN)
- Shandong First Medical University (CN)
- Fuzhou University (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-12-10
- DOI
- https://doi.org/10.3389/fphys.2025.1729997
- Primary Topic
- Bone Metabolism and Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Fujian Province
- Natural Science Foundation of Shandong Province