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Disclosure of interest: “Junji Fukumori: nothing to disclose”, “Kenji Fukutome: nothing to disclose”, “Shuta Aketa: nothing to disclose”, “Yasushi Motoyama: 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 P299 - ESOC25-2147 PREDICTING COGNITIVE IMPAIRMENT USING MACHINE LEARNING IN PATIENTS WITH CEREBRAL SMALL VESSEL DISEASES Tingting Mao 1 , Tingting Wang 2 , Yilong Wang 2 , Ling Guan 1,2 1 Beijing Institute of Technology, Beijing, China, 2 Beijing Tiantan Hospital, Beijing, China Background and Aims: Cerebral small vessel disease (CSVD) is a major cause of vascular cognitive impairment (VCI), yet predicting the progression of cognitive decline including different cognitive domains in patients with CSVD still remains challenge
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It said its consultations encouraged “shared decision-making, where individuals are given balanced information on potential mechanisms, theoretical benefits and uncertainties”
