NLP-based tools for localization of the epileptogenic zone in patients with drug-resistant focal epilepsy.

ABSTRACT: Epilepsy surgery is an option for people with focal onset drug-resistant (DR) seizures but a delayed or incorrect diagnosis of epileptogenic zone (EZ) location limits its efficacy. Seizure semiological manifestations and their chronological appearance contain valuable information on the putative EZ location but their interpretation relies on extensive experience. The aim of our work is to support the localization of EZ in DR patients automatically analyzing the semiological description of seizures contained in video-EEG reports. Our sample is composed of 536 descriptions of seizures extracted from Electronic Medical Records of 122 patients. We devised numerical representations of anamnestic records and seizures descriptions, exploiting Natural Language Processing (NLP) techniques, and used

SUBMITTER: Mora S 

PROVIDER: S-EPMC10825198 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature