An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage.

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ID: 128177
2020
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Abstract
Acute ischemic stroke constitutes approximately 85% of strokes. Most strokes occur in community settings; thus, automatic algorithms techniques are attractive for managing these cases. This article reviews the use of deep learning convolutional neural networks in the management of ischemic stroke. Artificial intelligence-based algorithms may be used in patient triage to detect and sound the alarm based on early imaging, alert care teams, and assist in treatment selection. This article reviews algorithms for artificial intelligence techniques that may be used to detect and localize acute ischemic stroke. We describe artificial intelligence algorithms for these tasks and illustrate them with examples.
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gupta2020anneuroimaging Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Gupta, Rajiv;Krishnam, Sanjith Prahas;Schaefer, Pamela W;Lev, Michael H;Gonzalez, R Gilberto;
Journal neuroimaging clinics of north america
Year 2020
DOI S1052-5149(20)30057-5
URL
Keywords
stroke ischemic stroke deep learning neural networks ischemic stroke detection stroke segmentation

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