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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Dades bibliogràfiques
Publicat a:Acta Neurochir (Wien)
Autors principals: 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
Format: Artigo
Idioma:Inglês
Publicat: Springer Vienna 2020
Matèries:
Original Article - Vascular Neurosurgery - Other
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC7593274/
https://ncbi.nlm.nih.gov/pubmed/32642833
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00701-020-04484-6
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