A machine learning-based fall-risk score for severity of fall-related adverse outcomes in community older adults
The ML-FRS could be used to screen for fall risk and fall-related adverse outcomes in community-dwelling older adults.
Authors
- Wei Lan (ORCID: https://orcid.org/0000-0001-5839-7504)
- Huihe Chen (ORCID: https://orcid.org/0000-0003-1911-4932)
- Lanhui Huang (ORCID: https://orcid.org/0000-0002-1030-9760)
- Zhu‐Xin Wei (ORCID: https://orcid.org/0000-0003-0630-1165)
- Ling Wang (ORCID: https://orcid.org/0000-0003-1005-2229)
- Zhao Wang (ORCID: https://orcid.org/0000-0002-6820-7505)
- Jianwen Xu (ORCID: https://orcid.org/0000-0002-8363-6260)
- Ming Gao (ORCID: https://orcid.org/0000-0002-3182-4331)
- T. Y. Ling
- Xuehai Guan
Institutions
- Guangxi University (CN)
- Guangxi Medical University (CN)
- Capital Medical University (CN)
- Peking University (CN)
- Beijing Jishuitan Hospital (CN)
- First People's Hospital of Yunnan Province (CN)
- Guangxi Science and Technology Department (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
Publication Details
- Journal
- BMC Geriatrics
- Published
- 2025-09-26
- DOI
- https://doi.org/10.1186/s12877-025-06371-0
- Citations
- 1
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 1.16
Funders
- Guangxi Zhuang Autonomous Region Health and Family Planning Commission