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Data-driven electrophysiological feature based on deep learning to detect epileptic seizures

Shota Yamamoto, Takufumi Yanagisawa, Ryohei Fukuma, Satoru Oshino, Naoki Tani, Hui Ming Khoo, Kohtaroh Edakawa, Maki Kobayashi, Masataka Tanaka, Yuya Fujita, Haruhiko Kishima

2021Journal of Neural Engineering18 citationsDOIOpen Access PDF

Abstract

We derived an iEEG feature from the trained Epi-Net, which identified the epileptic seizures with improved accuracy and might contribute to identification of the epileptogenic zone.

Topics & Concepts

EpilepsyIctalPattern recognition (psychology)Support vector machineFeature (linguistics)Epileptic seizureArtificial intelligenceElectroencephalographyComputer scienceReceiver operating characteristicConvolutional neural networkElectrophysiologyPhase lagAudiologyNeurosciencePsychologyMedicineMathematicsMachine learningApplied mathematicsPhilosophyLinguisticsEEG and Brain-Computer InterfacesEpilepsy research and treatmentFunctional Brain Connectivity Studies
Data-driven electrophysiological feature based on deep learning to detect epileptic seizures | Litcius