Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?
This study established a preliminary diagnostic model for osteoporosis, contributing to increased efficiency in diagnosing the disease.
Authors
- Pengran Liu (ORCID: https://orcid.org/0000-0003-4151-6014)
- Yanlin Su (ORCID: https://orcid.org/0000-0002-8407-006X)
- W. J. Zhu (ORCID: https://orcid.org/0009-0007-9879-1443)
- G. S. Huang
- Xu Guo (ORCID: https://orcid.org/0000-0002-0054-0870)
- Kaifang Chen (ORCID: https://orcid.org/0000-0003-4883-9991)
- Yizhou Wan (ORCID: https://orcid.org/0000-0002-5667-0762)
- Weijie Su (ORCID: https://orcid.org/0000-0003-1787-1219)
- Yulong Wang (ORCID: https://orcid.org/0000-0001-8148-3099)
- Lianxin Li (ORCID: https://orcid.org/0000-0001-5771-9241)
Institutions
- Union Hospital (HK)
- Shandong University (CN)
- Wuhan No.1 Hospital (CN)
- Shandong Provincial Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1186/s12911-025-02943-7
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 2.94
Funders
- National Natural Science Foundation of China