Explainable machine learning model for pre‐frailty risk assessment in community‐dwelling older adults
An accurate and interpretable pre-frailty risk assessment framework using state-of-the-art machine learning techniques and explanation methods has been developed. Our framework incorporates a wide range of features and determinants, allowing for a comprehensive and nuanced understanding of pre-frailty risk.
Authors
- Baoqin Liu
- Zongjiu Zhang (ORCID: https://orcid.org/0000-0002-8131-4014)
- Zijian Cao (ORCID: https://orcid.org/0000-0001-7294-6602)
- Nan Jiang (ORCID: https://orcid.org/0000-0003-1469-0375)
- Chenlin Du (ORCID: https://orcid.org/0000-0001-7039-8542)
- Zeyu Zhang (ORCID: https://orcid.org/0009-0005-1357-0146)
Institutions
- China-Japan Friendship Hospital (CN)
- Beijing Hua Xin Hospital (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Health care science
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/hcs2.120
- Citations
- 3
- Primary Topic
- Frailty in Older Adults
- Type
- article
- Field-Weighted Citation Impact
- 1.03