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...

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Bibliographic Details

Published in:	Chinese Journal of Contemporary Neurology & Neurosurgery Vol. 26; no. 3; pp. 227 - 235
Main Authors:	REN, Zhe, GAO, Jing, YUE, Meng-yan, ZHAO, Ting, WANG, Na, CHEN, Ya-nan, HAN, Xiong
Format:	research tables/charts Journal Article
Published:	Chinese Journal of Contemporary Neurology & Neurosurgery Mar2026
Online Access:	View this record in EBSCOhost