Deep Convolutional Neural Network Based Interictal-Preictal Electroencephalography Prediction: Application to Focal Cortical Dysplasia Type-II

Deep Convolutional Neural Network Based Interictal-Preictal Electroencephalography Prediction: Application to Focal Cortical Dysplasia Type-II

We aimed to differentiate between the interictal and preictal states in epilepsy patients with focal cortical dysplasia (FCD) type-II using deep learning-based classifiers based on intracranial electroencephalography (EEG). We also investigated the practical conditions for high interictal-preictal d...

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Bibliographic Details
Main Authors: Yoon Gi Chung, Yonghoon Jeon, Sun Ah Choi, Anna Cho, Hunmin Kim, Hee Hwang, Ki Joong Kim
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Neurology
Subjects:
epilepsy surgery
seizure prediction
focal cortical dysplasia
deep learning
convolutional neural networks
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2020.594679/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2020.594679/full

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