Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Predicting Discharge Disposition Following Meningioma Resection Using a Multi-Institutional Natural Language Processing Model
12
Zitationen
8
Autoren
2020
Jahr
Abstract
ML and NLP are underutilized in neurosurgery. Here, we construct a multi-institutional NLP model that predicts nonhome discharge.
Ähnliche Arbeiten
The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary
2016 · 15.692 Zit.
A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival
2001 · 3.038 Zit.
International subarachnoid aneurysm trial (ISAT) of neurosurgical clipping versus endovascular coiling in 2143 patients with ruptured intracranial aneurysms: a randomised comparison of effects on survival, dependency, seizures, rebleeding, subgroups, and aneurysm occlusion
2005 · 2.827 Zit.
SPREADING DEPRESSION OF ACTIVITY IN THE CEREBRAL CORTEX
1944 · 2.652 Zit.
CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012–2016
2019 · 2.575 Zit.