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Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Seizure prediction in epilepsy: from circadian concepts via probabilistic forecasting to statistical evaluation
Björn Schelter1, Hinnerk Feldwisch-Drentrup, Matthias Ihle
1Faculty of Mathematics and Physics, University of Freiburg, Freiburg, Germany. schelter@fdm.uni-freiburg.de
Abstract:
Seizure prediction performance is hampered by high numbers of false predictions. Here we present an approach to reduce the number of false predictions based on circadian concepts. Based on eight representative patients we demonstrate that this approach increases the performance considerably. The fraction of patients for whom we found a significant seizure prediction performance was increased from 25% to 38% by accounting for circadian dependencies.
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