Predictive Model of Internal Bleeding in Elderly Aspirin Users Using XGBoost Machine Learning
This study successfully developed a predictive model to estimate the risk of bleeding in elderly aspirin users. This model can serve as a potential useful tool for clinicians to estimate the risk of bleeding in elderly aspirin users and make informed decisions regarding their treatment and management.
Authors
- Tenggao Chen
- Wang Maofeng (ORCID: https://orcid.org/0000-0002-3166-0461)
- Wanlin Lei
Institutions
- Wenzhou Medical University (CN)
- Dongyang People's Hospital (CN)
Publication Details
- Journal
- Risk Management and Healthcare Policy
- Published
- 2024-09-01
- DOI
- https://doi.org/10.2147/rmhp.s478826
- Citations
- 7
- Primary Topic
- Antiplatelet Therapy and Cardiovascular Diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.81
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Zhejiang Province