Not one size fits all: Influence of EEG type when training a deep neural network for interictal epileptiform discharge detection

Not one size fits all: Influence of EEG type when training a deep neural network for interictal epileptiform discharge detection

Objective: Deep learning methods have shown potential in automating interictal epileptiform discharge (IED) detection in electroencephalograms (EEGs). While it is known that these algorithms are dependent on the type of data used for training, this has not been explicitly explored in EEG analysis ap...

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Bibliographic Details
Main Authors: Catarina da Silva Lourenço, Marleen C. Tjepkema-Cloostermans, Michel J.A.M. van Putten
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Deep learning
Convolutional neural networks
Epilepsy
Interictal epileptiform Discharges
Routine and ambulatory EEG
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914823001648

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http://www.sciencedirect.com/science/article/pii/S2352914823001648

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