Disclosure of interest: nothing to disclose Poster Session II - DIGITAL TRANSFORMATION, AI AND ROBOTICS 07.00 - DIGITAL TRANSFORMATION, AI AND ROBOTICS - 07.01 - TECHNOLOGY INNOVATIONS: ROBOTS, VIRTUAL REALITY, ARTIFICIAL INTELLIGENCE AND MORE P909 - ESOC25-201 NEUROLOGICAL SIGNS IDENTIFIED BY AI RELATED TO STROKE PATIENT RECANALIZATION Sofa Vargas Ibarra 1 , Vincent Vigneron 1 , Nicolas Chausson 2 , Hichem Maaref 1 , Sonia Garcia 3 , Didier Smadja 2 , Yann Lhermitte 2 1 IBISC Laboratory, Evry University, Paris-Saclay, Evry-Courcouronnes, France, 2 Centre Hospitalier Sud Francilien, Corbeil-Essonnes, France, 3 SAMOVAR, Tlcom SudParis, Institut Polytechnique de Paris, Palaiseau, France Background and Aims: Thrombus dimensions are critical factors influencing early recanalisation following thrombolysis in stroke patients and the Susceptibility Vessel Sign (SVS), a ferromagnetic artefact, reflects the composition of the thrombus [1] (iron content and therefore red blood cell content)
Ulnar neuropathy creates specific indicators that differ from deltoid pain
Unlike many other peptides, BPC-157 acts without binding to classic androgen or estrogen receptors, making it a unique subject for research into angiogenesis (blood vessel formation) and fibroblast migration
Rodriguez-Palacios A
It remains in Phase 3 clinical trials with approval expected in 2026-2027
