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Artificial Intelligence and Computational Approaches for Epilepsy

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 prov...

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Detalles Bibliográficos
Autores principales: An, Sora, Kang, Chaewon, Lee, Hyang Woon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Epilepsy Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494883/
https://www.ncbi.nlm.nih.gov/pubmed/32983950
http://dx.doi.org/10.14581/jer.20003
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author An, Sora
Kang, Chaewon
Lee, Hyang Woon
author_facet An, Sora
Kang, Chaewon
Lee, Hyang Woon
author_sort An, Sora
collection PubMed
description 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.
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spelling pubmed-74948832020-09-24 Artificial Intelligence and Computational Approaches for Epilepsy An, Sora Kang, Chaewon Lee, Hyang Woon J Epilepsy Res Review 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. Korean Epilepsy Society 2020-06-30 /pmc/articles/PMC7494883/ /pubmed/32983950 http://dx.doi.org/10.14581/jer.20003 Text en Copyright © 2020 Korean Epilepsy Society This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
An, Sora
Kang, Chaewon
Lee, Hyang Woon
Artificial Intelligence and Computational Approaches for Epilepsy
title Artificial Intelligence and Computational Approaches for Epilepsy
title_full Artificial Intelligence and Computational Approaches for Epilepsy
title_fullStr Artificial Intelligence and Computational Approaches for Epilepsy
title_full_unstemmed Artificial Intelligence and Computational Approaches for Epilepsy
title_short Artificial Intelligence and Computational Approaches for Epilepsy
title_sort artificial intelligence and computational approaches for epilepsy
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494883/
https://www.ncbi.nlm.nih.gov/pubmed/32983950
http://dx.doi.org/10.14581/jer.20003
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