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Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future

Artificial intelligence (AI) is increasingly used in medical image analysis and has accelerated scientific discoveries across fields of medicine. In this review, we highlight how AI has been applied to neuroimaging in patients with epilepsy to enhance classification of clinical diagnosis, prediction...

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Detalles Bibliográficos
Autores principales: Cendes, Fernando, McDonald, Carrie R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988724/
https://www.ncbi.nlm.nih.gov/pubmed/35444507
http://dx.doi.org/10.1177/15357597211068600
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author Cendes, Fernando
McDonald, Carrie R.
author_facet Cendes, Fernando
McDonald, Carrie R.
author_sort Cendes, Fernando
collection PubMed
description Artificial intelligence (AI) is increasingly used in medical image analysis and has accelerated scientific discoveries across fields of medicine. In this review, we highlight how AI has been applied to neuroimaging in patients with epilepsy to enhance classification of clinical diagnosis, prediction of treatment outcomes, and the understanding of cognitive comorbidities. We outline the strengths and shortcomings of current AI research and the need for future studies using large datasets that test the reproducibility and generalizability of current findings, as well as studies that test the clinical utility of AI approaches.
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spelling pubmed-89887242022-04-19 Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future Cendes, Fernando McDonald, Carrie R. Epilepsy Curr Current Review in Clinical Research Artificial intelligence (AI) is increasingly used in medical image analysis and has accelerated scientific discoveries across fields of medicine. In this review, we highlight how AI has been applied to neuroimaging in patients with epilepsy to enhance classification of clinical diagnosis, prediction of treatment outcomes, and the understanding of cognitive comorbidities. We outline the strengths and shortcomings of current AI research and the need for future studies using large datasets that test the reproducibility and generalizability of current findings, as well as studies that test the clinical utility of AI approaches. SAGE Publications 2022-01-12 /pmc/articles/PMC8988724/ /pubmed/35444507 http://dx.doi.org/10.1177/15357597211068600 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Current Review in Clinical Research
Cendes, Fernando
McDonald, Carrie R.
Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future
title Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future
title_full Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future
title_fullStr Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future
title_full_unstemmed Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future
title_short Artificial Intelligence Applications in the Imaging of Epilepsy and Its Comorbidities: Present and Future
title_sort artificial intelligence applications in the imaging of epilepsy and its comorbidities: present and future
topic Current Review in Clinical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988724/
https://www.ncbi.nlm.nih.gov/pubmed/35444507
http://dx.doi.org/10.1177/15357597211068600
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