Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography

Predicting seizure recurrence risk is critical to the diagnosis and management of epilepsy. Routine electroencephalography (EEG) is a cornerstone of the estimation of seizure recurrence risk. However, EEG interpretation relies on the visual identification of interictal epileptiform discharges (IEDs)...

Descripción completa

Detalles Bibliográficos
Autores principales: Lemoine, Émile, Toffa, Denahin, Pelletier-Mc Duff, Geneviève, Xu, An Qi, Jemel, Mezen, Tessier, Jean-Daniel, Lesage, Frédéric, Nguyen, Dang K., Bou Assi, Elie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403587/
https://www.ncbi.nlm.nih.gov/pubmed/37542101
http://dx.doi.org/10.1038/s41598-023-39799-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403587/
https://www.ncbi.nlm.nih.gov/pubmed/37542101
http://dx.doi.org/10.1038/s41598-023-39799-8

Ejemplares similares