Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage

BACKGROUND: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Machine learning (ML) defines modern data analysis te...

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Detalles Bibliográficos
Autores principales: Muscas, Giovanni, Matteuzzi, Tommaso, Becattini, Eleonora, Orlandini, Simone, Battista, Francesca, Laiso, Antonio, Nappini, Sergio, Limbucci, Nicola, Renieri, Leonardo, Carangelo, Biagio R., Mangiafico, Salvatore, Della Puppa, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2020
Materias:
Original Article - Vascular Neurosurgery - Other
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593274/
https://www.ncbi.nlm.nih.gov/pubmed/32642833
http://dx.doi.org/10.1007/s00701-020-04484-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593274/
https://www.ncbi.nlm.nih.gov/pubmed/32642833
http://dx.doi.org/10.1007/s00701-020-04484-6

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