The predictive value of light gradient boosting machine model based on three nonlinear features of scalp electroencephalography on the preictal phase of epilepsy.
Objective Constructing a classification model based on 3 nonlinear features of scalp electroencephalography (SEEG) for identifying the preictal phase of epilepsy. Methods Total 83 patients with epilepsy who underwent long - term SEEG monitoring at He'nan Provincial People's Hospital from January 201...
| Publicado en: | Chinese Journal of Contemporary Neurology & Neurosurgery Vol. 26; no. 3; pp. 227 - 235 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Chinese Journal of Contemporary Neurology & Neurosurgery
Mar2026
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| Acceso en línea: | Ver este registro en EBSCOhost |