The expert's knowledge combined with AI outperforms AI alone in seizure onset zone localization using resting state fMRI.

ABSTRACT: We evaluated whether integration of expert guidance on seizure onset zone (SOZ) identification from resting state functional MRI (rs-fMRI) connectomics combined with deep learning (DL) techniques enhances the SOZ delineation in patients with refractory epilepsy (RE), compared to utilizing DL alone. Rs-fMRI was collected from 52 children with RE who had subsequently undergone ic-EEG and then, if indicated, surgery for seizure control (n = 25). The resting state functional connectomics data were previously independently classified by two expert epileptologists, as indicative of measurement noise, typical resting state network connectivity, or SOZ. An expert knowledge integrated deep network was trained on functional connectomics data to identify SOZ. Expert knowledge integrated with D

SUBMITTER: Kamboj P 

PROVIDER: S-EPMC10808636 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature