Comparison of machine learning models for seizure prediction in hospitalized patients

Comparison of machine learning models for seizure prediction in hospitalized patients

Abstract Objective To compare machine learning methods for predicting inpatient seizures risk and determine the feasibility of 1‐h screening EEG to identify low‐risk patients (<5% seizures risk in 48 h). Methods The Critical Care EEG Monitoring Research Consortium (CCEMRC) multicenter database co...

Full description

Bibliographic Details
Main Authors: Aaron F. Struck, Andres A. Rodriguez‐Ruiz, Gamaledin Osman, Emily J. Gilmore, Hiba A. Haider, Monica B. Dhakar, Matthew Schrettner, Jong W. Lee, Nicolas Gaspard, Lawrence J. Hirsch, M. Brandon Westover, Critical Care EEG Monitoring Research Consortium (CCERMRC)
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:Annals of Clinical and Translational Neurology
Online Access:https://doi.org/10.1002/acn3.50817

Internet

https://doi.org/10.1002/acn3.50817

Similar Items