Identifying New Risk Associations Between Chronic Physical Illness and Mental Health Disorders in China: Machine Learning Approach to a Retrospective Population Analysis
Machine learning models can effectively be used to study the comorbidity between mental health disorders and chronic physical illnesses. The identified high-risk chronic physical illness categories for comorbidity, the correlations between disease combinations, and the variability of comorbidity patterns according to age and gender provide valuable insights into the complex relationship between these two types of disorders.
Authors
- Chao Che (ORCID: https://orcid.org/0000-0003-2978-5430)
- William Ollier (ORCID: https://orcid.org/0000-0001-6502-6584)
- Yonghong Peng (ORCID: https://orcid.org/0000-0002-5508-1819)
- Lei Liang (ORCID: https://orcid.org/0000-0003-3294-2978)
- Ti Liu
- Yao Lu (ORCID: https://orcid.org/0000-0001-9004-9569)
Institutions
- Manchester Metropolitan University (GB)
- Sun Yat-sen University (CN)
- Dalian University of Technology (CN)
- Dalian University (CN)
- Affiliated Hospital of Guangdong Medical College Hospital (CN)
- Anglia Ruskin University (GB)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-04-01
- DOI
- https://doi.org/10.2196/72599
- Citations
- 1
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 1.35