Machine learning of multimodal MRI to predict the development of epileptic seizures after traumatic brain injury

Marianna La Rocca, Rachael Garner, Kay Jann, Hosung Kim, Paul Vespa, Arthur W Toga, Dominique Duncan

Keywords: Machine learning, Random Forest, Support Vector Machine, FreeSurfer, Multi-Scale Entropy, Magnetic Resonance Imaging, Post-traumatic epilepsy.

TL;DR: Machine learning for the detection of MRI changes associated to seizure occurrence in Traumatic Brain Injury patients.

Abstract: One common consequence of Traumatic Brain Injury (TBI) that causes significant disability amongst patient populations is post-traumatic epilepsy (PTE). In this work, we use machine learning approaches to reveal subtle brain changes in Magnetic Resonance Images (MRIs) which may serve as PTE biomarkers.

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