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Deep into the Brain: Artificial Intelligence in Stroke Imaging

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient...

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Detalles Bibliográficos
Autores principales: Lee, Eun-Jae, Kim, Yong-Hwan, Kim, Namkug, Kang, Dong-Wha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Stroke Society 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647643/
https://www.ncbi.nlm.nih.gov/pubmed/29037014
http://dx.doi.org/10.5853/jos.2017.02054
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author Lee, Eun-Jae
Kim, Yong-Hwan
Kim, Namkug
Kang, Dong-Wha
author_facet Lee, Eun-Jae
Kim, Yong-Hwan
Kim, Namkug
Kang, Dong-Wha
author_sort Lee, Eun-Jae
collection PubMed
description Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.
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spelling pubmed-56476432017-10-23 Deep into the Brain: Artificial Intelligence in Stroke Imaging Lee, Eun-Jae Kim, Yong-Hwan Kim, Namkug Kang, Dong-Wha J Stroke Review Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives. Korean Stroke Society 2017-09 2017-09-29 /pmc/articles/PMC5647643/ /pubmed/29037014 http://dx.doi.org/10.5853/jos.2017.02054 Text en Copyright © 2017 Korean Stroke 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/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Lee, Eun-Jae
Kim, Yong-Hwan
Kim, Namkug
Kang, Dong-Wha
Deep into the Brain: Artificial Intelligence in Stroke Imaging
title Deep into the Brain: Artificial Intelligence in Stroke Imaging
title_full Deep into the Brain: Artificial Intelligence in Stroke Imaging
title_fullStr Deep into the Brain: Artificial Intelligence in Stroke Imaging
title_full_unstemmed Deep into the Brain: Artificial Intelligence in Stroke Imaging
title_short Deep into the Brain: Artificial Intelligence in Stroke Imaging
title_sort deep into the brain: artificial intelligence in stroke imaging
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647643/
https://www.ncbi.nlm.nih.gov/pubmed/29037014
http://dx.doi.org/10.5853/jos.2017.02054
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