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Pan B et al

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

55, 3323 (2016).CrossRefGoogle ScholarPubMed Hayashi, K., Maruhashi, T., Nakamura, M., Sakamoto, W., and Yogo, T.: One-pot synthesis of dual stimuli-responsive degradable hollow hybrid nanoparticles for image-guided trimodal therapy

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Molecular Replacement was then performed with the model of Apo MavL (PDB:6OMI) and Ub (PDB:6K11) as a template to determine the structure of the MavL-ADPR (PDB:8IPW) and MavL 40-404(D315A) -ADPR-Ub (PDB:8IPJ) complexes, respectively