Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy

no code implementations • 15 Dec 2018 • Yogatheesan Varatharajah, Brent Berry, Jan Cimbalnik, Vaclav Kremen, Jamie Van Gompel, Matt Stead, Benjamin Brinkmann, Ravishankar Iyer, Gregory Worrell

An ability to map seizure-generating brain tissue, i. e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy.

EEG

Convolutional Neural Networks for Epileptic Seizure Prediction

no code implementations • 2 Nov 2018 • Matthias Eberlein, Raphael Hildebrand, Ronald Tetzlaff, Nico Hoffmann, Levin Kuhlmann, Benjamin Brinkmann, Jens Müller

In this contribution, we present and discuss a novel methodology for the classification of intracranial electroencephalography (iEEG) for seizure prediction.

Binary Classification General Classification +1

EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms

no code implementations • NeurIPS 2017 • Yogatheesan Varatharajah, Min Jin Chong, Krishnakant Saboo, Brent Berry, Benjamin Brinkmann, Gregory Worrell, Ravishankar Iyer

This paper presents a probabilistic-graphical model that can be used to infer characteristics of instantaneous brain activity by jointly analyzing spatial and temporal dependencies observed in electroencephalograms (EEG).

EEG