Construct prediction models for low muscle mass with metabolic syndrome using machine learning
This study developed an interpretable ML model based on SHAP methodology to identify risk factors for low muscle mass in a young population of MetS patients. Additionally, a web-based tool was implemented to facilitate sarcopenia screening.
Authors
- Yuanxin Wu (ORCID: https://orcid.org/0000-0001-6941-615X)
- Li Fu (ORCID: https://orcid.org/0009-0002-1800-757X)
- Gongchang Yu (ORCID: https://orcid.org/0000-0002-2029-0960)
- Hao Chen (ORCID: https://orcid.org/0000-0002-2680-6921)
- Fan Hu (ORCID: https://orcid.org/0000-0002-0522-392X)
- Liang Shi (ORCID: https://orcid.org/0009-0007-5164-1245)
- Meng Yin (ORCID: https://orcid.org/0000-0002-8966-4051)
Institutions
- Shandong First Medical University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-09-09
- DOI
- https://doi.org/10.1371/journal.pone.0331925
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- State Administration of Traditional Chinese Medicine of the People's Republic of China
- Natural Science Foundation of Shandong Province
- Shandong First Medical University