Machine Learning Models to Predict Electroencephalographic Seizures in Critically Ill Children

OBJECTIVE: Determine whether machine learning techniques would enhance our ability to incorporate key variables into a parsimonious model with optimized prediction performance for electroencephalographic seizure (ES) prediction in critically ill children. METHODS: We analyzed data from a prospective...

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Detalhes bibliográficos
Publicado no:Seizure
Main Authors: Hu, Jian, Fung, France W., Jacobwitz, Marin, Parikh, Darshana S., Vala, Lisa, Donnelly, Maureen, Topjian, Alexis A., Abend, Nicholas S., Xiao, Rui
Formato: Artigo
Idioma:Inglês
Publicado em: 2021
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8044039/
https://ncbi.nlm.nih.gov/pubmed/33714840
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.seizure.2021.03.001
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