Scalp EEG-Based Automatic Detection of Epileptiform Events via Graph Convolutional Network and Bi-Directional LSTM Co-Embedded Broad Learning System-Reference-Cited by-同舟云学术

Scalp EEG-Based Automatic Detection of Epileptiform Events via Graph Convolutional Network and Bi-Directional LSTM Co-Embedded Broad Learning System

Author:

Liu Yang¹^ORCID,Zhou Huan²,Guan Min³,Feng Fengling²^ORCID,Duan Junwei¹^ORCID

Affiliation:

1. College of Information Science and Technology, Jinan University, Guangzhou, China

2. Neurological Function Examination Room, The First Affiliated Hospital of Jinan University, Guangzhou, China

3. Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, China

Funder

National Key R&D Program of China

Basic and Applied Basic Research Foundation of Guangdong Province

Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

Reference33 articles.

2. Time–frequency decomposition of scalp electroencephalograms improves deep learning-based epilepsy diagnosis;hangavel;Int J Neural Syst,2021

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