Predicting and explaining social isolation: insights from an interpretable machine learning model in ageing populations
With multimodal data, the GBM outperformed existing models for identifying social isolation risk. Its interpretability highlights actionable and potentially reversible targets, especially at community and environmental levels.
Authors
- Jianing Qiu
- Sicheng Li (ORCID: https://orcid.org/0009-0009-8832-0829)
- Ya Fang (ORCID: https://orcid.org/0000-0002-9895-3234)
- Kyle Lam (ORCID: https://orcid.org/0000-0001-6407-4912)
Institutions
- Xiamen University (CN)
- Mohamed bin Zayed University of Artificial Intelligence (AE)
- Imperial College London (GB)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- The Gerontologist
- Published
- 2025-12-09
- DOI
- https://doi.org/10.1093/geront/gnaf297
- Primary Topic
- Explainable Artificial Intelligence (XAI)
- Type
- article
- Field-Weighted Citation Impact
- 0.00