Cross-sectional study on smoking types and stroke risk: development of a predictive model for identifying stroke risk
This study reveals a significant association between smoking types and stroke risk. An XGBoost-based stroke prediction model was established, which has the potential to improve the accuracy of stroke risk assessment and contribute to personalized interventions for stroke prevention, thus alleviating the healthcare burden related to stroke.
Authors
- Ji Wen (ORCID: https://orcid.org/0000-0002-3327-5591)
- Minjia Yuan (ORCID: https://orcid.org/0000-0002-6145-2030)
- Chao Feng Ding (ORCID: https://orcid.org/0000-0002-3212-9103)
- Jiwei Cheng
Institutions
- Shanghai University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-03-24
- DOI
- https://doi.org/10.3389/fphys.2025.1528910
- Citations
- 2
- Primary Topic
- Cardiovascular Health and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 2.78