An explainable machine learning-based prediction model for sarcopenia in elderly Chinese people with knee osteoarthritis
From the perspective of public health and aging, this study constructed an interpretable sarcopenia risk prediction model on the basis of routine clinical data. This model can be used for early screening and risk assessment of symptomatic KOA patients, assisting health departments and clinicians in the early detection and follow-up of relevant populations, thereby improving the quality of life and health outcomes of elderly individuals.
Authors
- Yuqin Zhou (ORCID: https://orcid.org/0000-0002-7968-047X)
- Tao Yang (ORCID: https://orcid.org/0000-0002-9537-0500)
- Yi Zhou (ORCID: https://orcid.org/0000-0001-6560-1059)
- Kongfa Hu (ORCID: https://orcid.org/0000-0001-7670-3501)
- Ziyan Wang (ORCID: https://orcid.org/0000-0002-4085-249X)
- Xing Zeng (ORCID: https://orcid.org/0009-0002-4672-1439)
Institutions
- Nanjing University of Chinese Medicine (CN)
- Nanjing Health and Health Commission (CN)
- Jiangsu Province Hospital (CN)
Publication Details
- Journal
- Aging Clinical and Experimental Research
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1007/s40520-025-02931-x
- Citations
- 8
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 9.31
Funders
- National Key Research and Development Program of China