Disclosure of interest: Janos Szalma: nothing to disclose, Alessandro Delmonte: nothing to disclose, Jol Schaerer: nothing to disclose, David Scott: nothing to disclose, Luc Bracoud: nothing to disclose 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 P297 - ESOC25-2014 MULTIMODAL CT AND ARTIFICIAL INTELLIGENCE (AI) IN ENHANCING THE DIFFERENTIAL DIAGNOSIS OF STROKE AND STROKE MIMICS: 12-MONTH RESULTS OF A MULTICENTER STUDY Kateina Dvornkov 1 , Veronika Kuneov 2 , Svatopluk Ostr 3 , Lenka Brtov 3 , Martin bal 1 , Martin Reiser 3 , Linda MacHov 1 , Kristna Janotov 3 , Martin Sobotka 1 , Zuzana Hanzelkov 1 , Adela Konde 4 , Tomas Jonszta 2 , Jaroslav Havelka 2 , Ondrej Volny 1,2 , Michal Bar 1 1 Department of Neurology, University Hospital in Ostrava, Ostrava, Czech Republic, 2 Department of Imaging Methods, Faculty of Medicine, Ostrava University, Ostrava, Czech Republic, 3 Neurology Department, Regional Hospital esk Budjovice, esk Budjovice, Czech Republic, 4 Department of Applied Mathematics, Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, Ostrava, Czech Republic Background and Aims: This multicenter study explores the combination of multimodal CT imaging and artificial intelligence (AI) to tackle the challenge of distinguishing stroke mimics (SM) from acute ischemic stroke (AIS)
doi:10.1161/HYPERTENSIONAHA.125.26055
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& William McCormick Chair of the department of Biochemistry and Molecular Biology at The George Washington University School of Medicine and Health Sciences, where he has served since 1978
