Physical and mental health management for the older adult using XGBoost algorithm supported by new media technology: developing personalized health intervention plans using healthcare data from the CLHLS database
This study demonstrates the feasibility and effectiveness of combining topic modeling, deep learning, and machine learning for older adult health risk assessment. The proposed scheme enhances the accuracy and intelligence of health management services, aiding in chronic disease prevention and improving the overall quality of life for older adult individuals.
Authors
- Xin Ming (ORCID: https://orcid.org/0000-0002-9238-5950)
- Shiyuan Qu (ORCID: https://orcid.org/0009-0008-3563-2995)
- Jie Liao (ORCID: https://orcid.org/0009-0009-4716-660X)
- Zixi Wang (ORCID: https://orcid.org/0009-0007-9700-1307)
- Yutong Wang (ORCID: https://orcid.org/0000-0002-3194-2530)
- Xin Guan (ORCID: https://orcid.org/0000-0002-9129-327X)
- Enhui Li (ORCID: https://orcid.org/0009-0001-2739-6741)
Institutions
- University of Leicester (GB)
- Wuhan University (CN)
- Guangzhou University (CN)
- Anhui Xinhua University (CN)
- Guangzhou Xinhua University
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-05-30
- DOI
- https://doi.org/10.3389/fpubh.2025.1535056
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Office for Philosophy and Social Sciences
- National Social Science Fund of China