Penn Medicine Researchers Devise Post-Stroke Event Algorithm
A multidisciplinary team of researchers in neurocritical care, engineering, and informatics at the University of Pennsylvania have devised a new way to detect which stroke patients may be at risk of a serious adverse event following a ruptured brain aneurysm. This new, data-driven machine learning model, involves an algorithm for computers to combine results from various non-invasive tests to predict a secondary event. Preliminary results were released at the recent Neurocritical Care Society Annual Meeting in Philadelphia.
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