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...

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Detalles Bibliográficos
Autores principales: Abedi, Vida, Avula, Venkatesh, Chaudhary, Durgesh, Shahjouei, Shima, Khan, Ayesha, Griessenauer, Christoph J, Li, Jiang, Zand, Ramin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003970/
https://www.ncbi.nlm.nih.gov/pubmed/33804724
http://dx.doi.org/10.3390/jcm10061286

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003970/
https://www.ncbi.nlm.nih.gov/pubmed/33804724
http://dx.doi.org/10.3390/jcm10061286

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