Machine Learning–Based Model for Prediction of Post-Stroke Cognitive Impairment in Acute Ischemic Stroke: A Cross-Sectional Study
Machine learning algorithms may be useful in the prediction of PSCI, especially logistic regression algorithms. In the present study, aging and hyperglycemia were independent risk factors for PSCI, and the cognition of such patients should be carefully addressed in clinical practice screening work.
Authors
- Junqin Zhang (ORCID: https://orcid.org/0000-0003-0335-4720)
- Zhaohong Kong (ORCID: https://orcid.org/0000-0001-6020-7992)
- Songlin Hong
- Zhentao Zhang (ORCID: https://orcid.org/0000-0001-6708-1472)
Institutions
- Wuhan University (CN)
- Renmin Hospital of Wuhan University (CN)
Publication Details
- Journal
- Neurology India
- Published
- 2024-11-01
- DOI
- https://doi.org/10.4103/ni.ni_987_21
- Citations
- 3
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 1.16