STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG

Abstract Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and partially subjective. Automatic, data-driven detect...

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Bibliographic Details
Main Authors: Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Automatic interictal epileptiform discharges detection
Convolutional Neural Networks
Deep Learning
Epilepsy
Magnetoencephalography
Online Access:https://doi.org/10.1038/s41598-025-03880-1
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https://doi.org/10.1038/s41598-025-03880-1

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