Lee Eun-Jae, Kim Yong-Hwan, Kim Namkug, Kang Dong-Wha
Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
J Stroke. 2017 Sep;19(3):277-285. doi: 10.5853/jos.2017.02054. Epub 2017 Sep 29.
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.
人工智能(AI)是一种旨在模仿人类智能的计算机系统,正越来越受到关注,并被应用于包括医学在内的许多领域。中风医学就是AI的一个应用领域,用于提高诊断准确性和患者护理质量。对于中风管理而言,对中风影像学进行充分分析至关重要。最近,AI技术已被应用于解读中风影像学数据,并取得了一些有前景的成果。在不久的将来,此类AI技术可能会在以个体化方式确定中风患者的治疗方法和预测预后方面发挥关键作用。在本综述中,我们简要介绍AI在中风影像学中的应用,特别关注其技术原理、临床应用和未来前景。