Development and Application of a Machine Learning-Based Predictive Model for Carotid Restenosis After Interventional Surgery in Elderly Ischemic Stroke Patients
Our research showed that compared with other machine learning algorithms, the GBM model demonstrates the best accuracy and stability in predicting the risk of carotid restenosis after interventional surgery in elderly ischemic stroke patients, and it has high clinical application value.
Authors
- Yanchun Jiang
- Xianmei Wu
- Xiaoyan Wang (ORCID: https://orcid.org/0000-0001-7406-5008)
- Yanbo Zhang (ORCID: https://orcid.org/0000-0003-1054-9657)
- Bo Jiang (ORCID: https://orcid.org/0000-0002-2041-8987)
- Hung‐Chih Lin (ORCID: https://orcid.org/0000-0002-8111-8371)
Institutions
- The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
- Nanxi Mountain Hospital (CN)
- The Stables (GB)
Publication Details
- Journal
- The Neurologist
- Published
- 2025-06-11
- DOI
- https://doi.org/10.1097/nrl.0000000000000627
- Primary Topic
- Cerebrovascular and Carotid Artery Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00