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Neuroimaging Clin. N. Am. · Nov 2020
ReviewArtificial Intelligence and Stroke Imaging: A West Coast Perspective.
- Guangming Zhu, Bin Jiang, Hui Chen, Elizabeth Tong, Yuan Xie, Tobias D Faizy, Jeremy J Heit, Greg Zaharchuk, and Max Wintermark.
- Department of Neuroradiology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, USA.
- Neuroimaging Clin. N. Am. 2020 Nov 1; 30 (4): 479-492.
AbstractArtificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intense research. AI techniques are well-suited for dealing with vast amounts of stroke imaging data and a large number of multidisciplinary approaches used in classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. This article addresses this topic and seeks to present an overview of machine learning and/or deep learning applied to stroke imaging.Copyright © 2020 Elsevier Inc. All rights reserved.
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