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KMID : 1142120170190030277
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Journal of Stroke
2017 Volume.19 No. 3 p.277 ~ p.285
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Deep into the Brain: Artificial Intelligence in Stroke Imaging
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Lee Eun-Jae
Kim Yong-Hwan
Kim Nam-Kug
Kang Dong-Wha
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Abstract
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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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KEYWORD
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Artificial intelligence, Machine learning, Stroke
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