Application of interpretable machine learning to predict activities of daily living disability in sarcopenia: insights from the CHARLS dataset
The IML-based model provides a scientific basis for developing health management strategies aimed at reducing ADL disability in older adults with sarcopenia, thereby improving quality of life and easing societal and familial care burdens.
Authors
- Zixian Song
- Ying Yang (ORCID: https://orcid.org/0009-0009-8063-4938)
- Ze Zhang (ORCID: https://orcid.org/0000-0002-3877-551X)
- Tingting Pan (ORCID: https://orcid.org/0000-0002-1673-6800)
Institutions
- Liaoning University of Traditional Chinese Medicine (CN)
- Affiliated Hospital of Taishan Medical University (CN)
- Affiliated Hospital of Liaoning University of Traditional Chinese Medicine (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- BMC Geriatrics
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1186/s12877-025-06542-z
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- State Administration of Traditional Chinese Medicine of the People's Republic of China