Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography

Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography

Abstract Predicting seizure recurrence risk is critical to the diagnosis and management of epilepsy. Routine electroencephalography (EEG) is a cornerstone of the estimation of seizure recurrence risk. However, EEG interpretation relies on the visual identification of interictal epileptiform discharg...

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Bibliographic Details
Main Authors: Émile Lemoine, Denahin Toffa, Geneviève Pelletier-Mc Duff, An Qi Xu, Mezen Jemel, Jean-Daniel Tessier, Frédéric Lesage, Dang K. Nguyen, Elie Bou Assi
Format: Article
Language:English
Published: Nature Portfolio 2023-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-39799-8

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https://doi.org/10.1038/s41598-023-39799-8

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