Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1783272280518819840 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5647643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Korean Stroke Society |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT leeeunjae deepintothebrainartificialintelligenceinstrokeimaging AT kimyonghwan deepintothebrainartificialintelligenceinstrokeimaging AT kimnamkug deepintothebrainartificialintelligenceinstrokeimaging AT kangdongwha deepintothebrainartificialintelligenceinstrokeimaging |