Poster Session I - DIGITAL TRANSFORMATION, AI AND ROBOTICS 07.00 - DIGITAL TRANSFORMATION, AI AND ROBOTICS - 07.01 - TECHNOLOGY INNOVATIONS: ROBOTS, VIRTUAL REALITY, ARTIFICIAL INTELLIGENCE AND MORE P303 - ESOC25-1163 DEEP LEARNING-BASED PREDICTION OF INFARCT GROWTH IN ACUTE ISCHEMIC STROKE PATIENTS: ANALYSIS OF AN EXPANDED COHORT Ewout Heylen 1,2 , Anke Wouters 3 , Soren Christensen 2 , Nicole Yuen 2 , Pierre Seners 4,5 , Lieselotte Vandewalle 2,3,6 , Michael Mlynash 2 , Stephanie Kemp 2 , Jelle Demeestere 3,6 , Jeremy Heit 2 , Greg Albers 2 , Frederik Maes 1 , Maarten Lansberg 2 , Robin Lemmens 3,6 1 Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium, 2 Stanford Stroke Center, Palo Alto, United States, 3 Division of Experimental Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium, 4 Department of Neurology, Hpital Fondation A
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Infection signs, worsening injuries, or unusual neurologic symptoms need symptom-based review
albicans toxin, destroy the gut mucosal barrier, and invade the blood, resulting in sepsis and multiple organ insufficiency, both of which are fatal [5]
