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Artificial intelligence and machine learning tools can augment stroke management across the continuum of care, including prevention, prognostication, neuroimaging, diagnosis, treatment, and recovery. Andrea Becerril Gaitan, MD; Kalina A. Misiolek, MD; Emily F. Fisher, MD, MPH; Natasha T. Ironside, MD; and Andrew M. Southerland, MD, MSc.
22 lip 2020 · Graphical overview of the main applications of artificial intelligence (AI) in acute ischemic stroke. During the acute phase, the main interest is in supporting detection of key imaging characteristics such as presence of large vessel occlusion, presence of hemorrhage, and volume of irreversibly damaged and potentially salvageable tissue.
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To propose standardized and feasible imaging protocols for constructing artificial intelligence (AI) database in acute stroke by assessing the current practice at tertiary hospitals in South Korea and reviewing evolving AI models.
27 paź 2020 · For example, an AI-based system can alert physicians of drug interactions and side effects. AI systems can also help stroke neurologists identify patients with anterior circulation large vessel occlusions and determine in real-time which candidates should be selected for revascularization.
26 lis 2020 · Artificial intelligence can help with various aspects of the stroke treatment paradigm, including infarct or hemorrhage detection, segmentation, classification, large vessel occlusion detection, Alberta Stroke Program Early CT Score grading, and prognostication.
25 sie 2020 · An automated, computer-assisted screening tool that can be seamlessly integrated into clinical workflow to quickly analyze patient symptoms and clinical data and suggest a diagnosis of stroke (‘StrokeAlert’ pop-up) in an ED setting could be valuable.
