Risk for post-stroke dangers flagged by new data-driven machine learning method

Written on:October 7, 2013
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A team of experts in neurocritical care, engineering, and informatics, with the Perelman School of Medicine 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…

Source: Medical Devices


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