Causal brain activity modeling for the understanding of epilepsy pathogenesis
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Date
2022
Authors
Garkot, Sofiya
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Abstract
Epilepsy affects 1% of the world’s population yearly and is one of the
most widespread diseases. Although some forms of epilepsy are effectively
treated using a medication, nearly every third patient needs surgical intervention
to remove the epileptogenic area.
This study examined an epileptic brain’s activity during the hallmarks
of epileptic activity - interictal epileptiform discharges (IEDs) - using Causal
Bayesian Networks. Results showed that trends of causal activity increase
before an IED and decrease afterwards, differentiating across awareness states.
Another benefit of the study is the recommendation system for a clinician
while evaluating the epileptogenic region. The channels that have most frequently
been a cause of an IED are reported as a potential resection area.
The code is freely available on the Github repository with the corresponding
documentation for a clinician.
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Citation
Garkot Sofiya. Causal brain activity modeling for the understanding of epilepsy pathogenesis. Bachelor Thesis. Ukrainian Catholic University, Faculty of Applied Sciences, Department of Computer Sciences. Lviv 2022, 39 p.