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In Neuroimaging clinics of North America

Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolutional neural networks for managing hemorrhagic stroke. Such a capability may be used to alert appropriate care teams, make decisions about patient transport from a primary care center to a comprehensive stroke center, and assist in treatment selection. This article reviews artificial intelligence algorithms for intracranial hemorrhage detection, quantification, and prognostication. Multiple algorithms currently being explored are described and illustrated with the help of examples.

Gupta Rajiv, Krishnam Sanjith Prahas, Schaefer Pamela W, Lev Michael H, Gilberto Gonzalez R


Deep learning neural networks, Hemorrhage expansion, Hemorrhagic stroke, Intracranial hemorrhage detection, Intracranial hemorrhage quantification, Stroke