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Full-Text Articles in Medicine and Health Sciences
Machine Learning Automated Detection Of Large Vessel Occlusion From Mobile Stroke Unit Computed Tomography Angiography, Alexandra L Czap, Mersedeh Bahr-Hosseini, Noopur Singh, Jose-Miguel Yamal, May Nour, Stephanie Parker, Youngran Kim, Lucas Restrepo, Rania Abdelkhaleq, Sergio Salazar-Marioni, Kenny Phan, Ritvij Bowry, Suja S Rajan, James C Grotta, Jeffrey L Saver, Luca Giancardo, Sunil A Sheth
Machine Learning Automated Detection Of Large Vessel Occlusion From Mobile Stroke Unit Computed Tomography Angiography, Alexandra L Czap, Mersedeh Bahr-Hosseini, Noopur Singh, Jose-Miguel Yamal, May Nour, Stephanie Parker, Youngran Kim, Lucas Restrepo, Rania Abdelkhaleq, Sergio Salazar-Marioni, Kenny Phan, Ritvij Bowry, Suja S Rajan, James C Grotta, Jeffrey L Saver, Luca Giancardo, Sunil A Sheth
Journal Articles
BACKGROUND: Prehospital automated large vessel occlusion (LVO) detection in Mobile Stroke Units (MSUs) could accelerate identification and treatment of patients with LVO acute ischemic stroke. Here, we evaluate the performance of a machine learning (ML) model on CT angiograms (CTAs) obtained from 2 MSUs to detect LVO.
METHODS: Patients evaluated on MSUs in Houston and Los Angeles with out-of-hospital CTAs were identified. Anterior circulation LVO was defined as an occlusion of the intracranial internal carotid artery, middle cerebral artery (M1 or M2), or anterior cerebral artery vessels and determined by an expert human reader. A ML model to detect LVO …