잠시만 기다려 주세요. 로딩중입니다.

Artificial Intelligence and Computational Approaches for Epilepsy

Journal of Epilepsy Research 2020년 10권 1호 p.8 ~ 17
안소라, 강채원, 이향운,
소속 상세정보
안소라 ( An So-Ra ) - Ewha Womans University School of Medicine Department of Neurology
강채원 ( Kang Chae-Won ) - Ewha Womans University School of Medicine Department of Neurology
이향운 ( Lee Hyang-Woon ) - Ewha Womans University School of Medicine Department of Neurology

Abstract


Studies on treatment of epilepsy have been actively conducted in multiple avenues, but there are limitations in improving its efficacy due to between-subject variability in which treatment outcomes vary from patient to patient. Accordingly, there is a growing interest in precision medicine that provides accurate diagnosis for seizure types and optimal treatment for an individual epilepsy patient. Among these approaches, computational studies making this feasible are rapidly progressing in particular and have been widely applied in epilepsy. These computational studies are being conducted in two main streams: 1) artificial intelligence-based studies implementing computational machines with specific functions, such as automatic diagnosis and prognosis prediction for an individual patient, using machine learning techniques based on large amounts of data obtained from multiple patients and 2) patient-specific modeling-based studies implementing biophysical in-silico platforms to understand pathological mechanisms and derive the optimal treatment for each patient by reproducing the brain network dynamics of the particular patient per se based on individual patient’s data. These computational approaches are important as it can integrate multiple types of data acquired from patients and analysis results into a single platform. If these kinds of methods are efficiently operated, it would suggest a novel paradigm for precision medicine.

키워드

Epilepsy; Precision medicine; Seizures; Artificial intelligence; Patient-specific modeling

원문 및 링크아웃 정보

등재저널 정보