Abbreviations: V: vehicle, CS: CagriSema, and WM: Weight matched
doi: 10.1038/s41584-020-0374-8
Disclosure of interest: None E-Posters - DIGITAL TRANSFORMATION, AI AND ROBOTICS 07.00 - DIGITAL TRANSFORMATION, AI AND ROBOTICS - 07.01 - TECHNOLOGY INNOVATIONS: ROBOTS, VIRTUAL REALITY, ARTIFICIAL INTELLIGENCE AND MORE P2596 - ESOC25-1195 MACHINE LEARNINGBASED EXPLAINABLE AUTOMATED NONLINEARCOMPUTATION SCORING SYSTEM FOR HEALTH SCORE AND AN APPLICATIONFOR PREDICTION OF PERIOPERATIVE STROKE: RETROSPECTIVE STUDY Mi-Young Oh 1 , Hee-Soo Kim 2 , Seung-Bo Lee 2 , Seung Mi Lee 3 1 Sejong General Hospital, Bucheon-si, South Korea, 2 Keimyung University School of Medicine, Daegu, South Korea, 3 Seoul National University College of Medicine, Seoul, South Korea Background and Aims: Machine learning (ML) has the potential to enhance performance by capturing nonlinear interactions
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