Machine Learning for Localizing Epileptogenic-Zone in the Temporal Lobe: Quantifying the Value of Multimodal Clinical-Semiology and Imaging Concordance

Machine Learning for Localizing Epileptogenic-Zone in the Temporal Lobe: Quantifying the Value of Multimodal Clinical-Semiology and Imaging Concordance

Background: Epilepsy affects 50 million people worldwide and a third are refractory to medication. If a discrete cerebral focus or network can be identified, neurosurgical resection can be curative. Most excisions are in the temporal-lobe, and are more likely to result in seizure-freedom than extra-...

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Bibliographic Details
Main Authors: Ali Alim-Marvasti, Fernando Pérez-García, Karan Dahele, Gloria Romagnoli, Beate Diehl, Rachel Sparks, Sebastien Ourselin, Matthew J. Clarkson, John S. Duncan
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Digital Health
Subjects:
epilepsy surgery
machine learning
semiology
hippocampal sclerosis
epileptogenic zone
temporal lobe epilepsy
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2021.559103/full

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https://www.frontiersin.org/articles/10.3389/fdgth.2021.559103/full

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