Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.
Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE). Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of ep...
Guardado en:
Autores principales: | Rubén Armañanzas, Lidia Alonso-Nanclares, Jesús Defelipe-Oroquieta, Asta Kastanauskaite, Rafael G de Sola, Javier Defelipe, Concha Bielza, Pedro Larrañaga |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2013
|
Materias: | |
Acceso en línea: | https://doaj.org/article/07b67b0f32464265bc7759cb2a5ca409 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Stability of synchronization clusters and seizurability in temporal lobe epilepsy.
por: Agostina Palmigiano, et al.
Publicado: (2012) -
Temporal Lobe Epilepsy and Psychiatric Comorbidity
por: Valerio Vinti, et al.
Publicado: (2021) -
Relationship between remnant hippocampus and amygdala and memory outcomes after stereotactic surgery for mesial temporal lobe epilepsy
por: Malikova H, et al.
Publicado: (2015) -
Occult focal cortical dysplasia may predict poor outcome of surgery for drug-resistant mesial temporal lobe epilepsy.
por: Arkadiusz Nowak, et al.
Publicado: (2021) -
Food intake precipitates seizures in temporal lobe epilepsy
por: Dalma Tényi, et al.
Publicado: (2021)