As it was previously mentioned the secondary outcome measures observed by the researchers included gastrocnemius muscle mass and foot flexion contractures
So while this comparison raised questions about how the treatment stacks up against competitors, it doesnt necessarily affect its chances of approval

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)

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