Comparison of machine learning models for seizure prediction in hospitalized patients

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 contains...

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Detalles Bibliográficos
Autores principales: Struck, Aaron F., Rodriguez‐Ruiz, Andres A., Osman, Gamaledin, Gilmore, Emily J., Haider, Hiba A., Dhakar, Monica B., Schrettner, Matthew, Lee, Jong W., Gaspard, Nicolas, Hirsch, Lawrence J., Westover, M. Brandon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6649418/
https://www.ncbi.nlm.nih.gov/pubmed/31353866
http://dx.doi.org/10.1002/acn3.50817

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6649418/
https://www.ncbi.nlm.nih.gov/pubmed/31353866
http://dx.doi.org/10.1002/acn3.50817

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