An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and
Rajiv Gupta1, Sanjith Prahas Krishnam2, Pamela W Schaefer1
1Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Harvard Medical School, Room: GRB-273A, 55 Fruit Street, Boston, MA 02114, USA.
Abstract:
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.
