The progress of the application of machine learning in epilepsy
10.3760/cma.j.cn113694-20230802-00031
- VernacularTitle:机器学习在癫痫方面的应用进展
- Author:
Zhiyuan DONG
1
;
Yong YANG
;
Yue YU
;
Yan WANG
Author Information
1. 青岛大学附属医院神经内科，青岛266000
- Keywords:
Epilepsy;
Electroencephalography;
Machine learning;
Anti-seizure medication
- From:
Chinese Journal of Neurology
2024;57(2):185-191
- CountryChina
- Language:Chinese
-
Abstract:
Epilepsy is an episodic, transient, stereotypic brain dysfunction caused by highly synchronized abnormal neuronal discharges in the brain, with unpredictable timing of seizures, for which the main treatment modalities are antiepileptic drugs and surgery. Its diagnosis and treatment require a large number of aids and clinical experience. For multiple clinical aspects of epilepsy, such as seizure prediction, drug therapy prognosis, and surgical treatment evaluation, machine learning can incorporate multiple clinical and imaging factors through deep mining of data, establish corresponding learning models, improve the efficiency and accuracy of epilepsy diagnosis, realize individualized application of antiepileptic drugs, and improve the preoperative evaluation and prognosis of epilepsy patients.
