Machine learning applications for electroencephalograph signals in epilepsy: a quick review
Author:
Open Access
- 29 April 2020
- journal article
- review article
- Published by Springer Nature in Acta Epileptologica
- Vol. 2 (1) , 1-7
Abstract
Machine learning (ML) is a fundamental concept in the field of state-of-the-art artificial intelligence (AI). Over the past two decades, it has evolved rapidly and been employed wildly in many fields. In medicine the widespread usage of ML has been observed in recent years. The present review examines various ML approaches for electroencephalograph (EEG) signal procession in epilepsy research, highlighting applications in the aspect of automated seizure detection, prediction and orientation. The present review also presents advantage, challenge and future direction of ML techniques in the analysis of EEG signals in epilepsy.Keywords
Funding Information
- National Natural Science Foundation of China (NO.81701269)
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