Deep into the Brain: Artificial Intelligence in Stroke Imaging.
- Author:
Eun Jae LEE
1
;
Yong Hwan KIM
;
Namkug KIM
;
Dong Wha KANG
Author Information
- Publication Type:Review
- Keywords: Artificial intelligence; Machine learning; Stroke
- MeSH: Artificial Intelligence*; Brain*; Computer Systems; Diagnosis; Humans; Intelligence; Machine Learning; Patient Care; Prognosis; Stroke*
- From:Journal of Stroke 2017;19(3):277-285
- CountryRepublic of Korea
- Language:English
- Abstract: 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.
