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Abstract #3245

Classification Between Epilepsy Patients and Healthy Controls Using Multi-Modal Structure-Function Brain Network

Yael Jacob1, Gaurav Verma1, Lara Marcuse1, Madeline Fields1, and Priti Balchandani1
1Icahn School of Medicine at Mount Sinai, New York, NY, United States

Epilepsy patients (EP) endure harmful effects both on their health and quality of life. Early identification of these individuals would be incredibly helpful to gauge management and expectations. Implementing a novel multilayer network analysis, considering communication within functional and structural networks as well as the interactions between them, we tested whether this whole-brain comprehensive network hierarchy can be used as predictors of epilepsy. Using multilayer network features as predictors in a machine learning algorithm we were able to classify EP and controls with overall accuracy of 84%, demonstrating the applicability of multi-modal imaging for diagnostics of epilepsy.

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