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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

This results in the loss of an appreciable part of the cell death machinery, which determines the uniqueness of cell death pathways in mature erythrocytes

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