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Prediction of Long-Term Stroke Recurrence Using Machine Learning Models
Background: The long-term risk of recurrent ischemic stroke, estimated to be between 17% and 30%, cannot be reliably assessed at an individual level. Our goal was to study whether machine-learning can be trained to predict stroke recurrence and identify key clinical variables and assess whether perf...
Guardado en:
| Publicado en: | J Clin Med |
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| Autores principales: | , , , , , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8003970/ https://ncbi.nlm.nih.gov/pubmed/33804724 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/jcm10061286 |
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