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Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape
Epilepsy, a neurological disorder characterized by recurrent seizures, has witnessed a remarkable transformation in its classification paradigm, driven by advances in clinical understanding, neuroimaging, and molecular genetics. This narrative review navigates the dynamic landscape of epilepsy class...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624359/ https://www.ncbi.nlm.nih.gov/pubmed/37927689 http://dx.doi.org/10.7759/cureus.46470 |
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author | Abdelsamad, Alaa Kachhadia, Meet Popatbhai Hassan, Talha Kumar, Lakshya Khan, Faisal Kar, Indrani Panta, Uttam Zafar, Wirda Sapna, FNU Varrassi, Giustino Khatri, Mahima Kumar, Satesh |
author_facet | Abdelsamad, Alaa Kachhadia, Meet Popatbhai Hassan, Talha Kumar, Lakshya Khan, Faisal Kar, Indrani Panta, Uttam Zafar, Wirda Sapna, FNU Varrassi, Giustino Khatri, Mahima Kumar, Satesh |
author_sort | Abdelsamad, Alaa |
collection | PubMed |
description | Epilepsy, a neurological disorder characterized by recurrent seizures, has witnessed a remarkable transformation in its classification paradigm, driven by advances in clinical understanding, neuroimaging, and molecular genetics. This narrative review navigates the dynamic landscape of epilepsy classification, offering insights into recent developments, challenges, and the promising horizon. Historically, epilepsy classification relied heavily on clinical observations, categorizing seizures based on their phenomenology and presumed etiology. However, the field has profoundly shifted from a symptom-based approach to a more refined, multidimensional system. One pivotal aspect of this evolution is the integration of neuroimaging techniques, particularly magnetic resonance imaging (MRI) and functional imaging modalities. These tools have unveiled the intricate neural networks implicated in epilepsy, facilitating the identification of distinct brain abnormalities and the categorization of epilepsy subtypes based on structural and functional findings. Furthermore, the role of genetics has become increasingly prominent in epilepsy classification. Genetic discoveries have not only unraveled the molecular underpinnings of various epileptic syndromes but have also provided valuable diagnostic and prognostic insights. This narrative review delves into the expanding realm of genetic testing and its impact on tailoring treatment strategies to individual patients. As the classification landscape evolves, there are accompanying challenges. The narrative review underscores the transformative potential of artificial intelligence and machine learning in epilepsy classification. These technologies hold promise in automating the analysis of complex neuroimaging and genetic data, offering enhanced accuracy and efficiency in epilepsy diagnosis and classification. In conclusion, navigating the shifting landscape of epilepsy classification is a journey marked by progress, complexity, and the prospect of improved patient care. We are charting a course toward more precise diagnoses and tailored treatments by embracing advanced neuroimaging, genetics, and innovative technologies. As the field continues to evolve, collaborative efforts and a holistic understanding of epilepsy's diverse manifestations will be instrumental in harnessing the full potential of this dynamic landscape. |
format | Online Article Text |
id | pubmed-10624359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-106243592023-11-04 Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape Abdelsamad, Alaa Kachhadia, Meet Popatbhai Hassan, Talha Kumar, Lakshya Khan, Faisal Kar, Indrani Panta, Uttam Zafar, Wirda Sapna, FNU Varrassi, Giustino Khatri, Mahima Kumar, Satesh Cureus Neurology Epilepsy, a neurological disorder characterized by recurrent seizures, has witnessed a remarkable transformation in its classification paradigm, driven by advances in clinical understanding, neuroimaging, and molecular genetics. This narrative review navigates the dynamic landscape of epilepsy classification, offering insights into recent developments, challenges, and the promising horizon. Historically, epilepsy classification relied heavily on clinical observations, categorizing seizures based on their phenomenology and presumed etiology. However, the field has profoundly shifted from a symptom-based approach to a more refined, multidimensional system. One pivotal aspect of this evolution is the integration of neuroimaging techniques, particularly magnetic resonance imaging (MRI) and functional imaging modalities. These tools have unveiled the intricate neural networks implicated in epilepsy, facilitating the identification of distinct brain abnormalities and the categorization of epilepsy subtypes based on structural and functional findings. Furthermore, the role of genetics has become increasingly prominent in epilepsy classification. Genetic discoveries have not only unraveled the molecular underpinnings of various epileptic syndromes but have also provided valuable diagnostic and prognostic insights. This narrative review delves into the expanding realm of genetic testing and its impact on tailoring treatment strategies to individual patients. As the classification landscape evolves, there are accompanying challenges. The narrative review underscores the transformative potential of artificial intelligence and machine learning in epilepsy classification. These technologies hold promise in automating the analysis of complex neuroimaging and genetic data, offering enhanced accuracy and efficiency in epilepsy diagnosis and classification. In conclusion, navigating the shifting landscape of epilepsy classification is a journey marked by progress, complexity, and the prospect of improved patient care. We are charting a course toward more precise diagnoses and tailored treatments by embracing advanced neuroimaging, genetics, and innovative technologies. As the field continues to evolve, collaborative efforts and a holistic understanding of epilepsy's diverse manifestations will be instrumental in harnessing the full potential of this dynamic landscape. Cureus 2023-10-04 /pmc/articles/PMC10624359/ /pubmed/37927689 http://dx.doi.org/10.7759/cureus.46470 Text en Copyright © 2023, Abdelsamad et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Neurology Abdelsamad, Alaa Kachhadia, Meet Popatbhai Hassan, Talha Kumar, Lakshya Khan, Faisal Kar, Indrani Panta, Uttam Zafar, Wirda Sapna, FNU Varrassi, Giustino Khatri, Mahima Kumar, Satesh Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape |
title | Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape |
title_full | Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape |
title_fullStr | Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape |
title_full_unstemmed | Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape |
title_short | Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape |
title_sort | charting the progress of epilepsy classification: navigating a shifting landscape |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624359/ https://www.ncbi.nlm.nih.gov/pubmed/37927689 http://dx.doi.org/10.7759/cureus.46470 |
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