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Disclosure of interest: NO 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 P308 - ESOC25-442 CLINICIAN PERSPECTIVES ON MACHINE LEARNING TOOLS FOR OUTCOME PREDICTION AND DECISION-MAKING IN INTRACEREBRAL HAEMORRHAGE Alexandra Hurden 1 , Menglu Ouyang, Leibo Liu 1,2 , Xiaoying Chen 1 , Craig Anderson 1 The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia, 2 Centre for Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, Australia Background and Aims: Machine learning (ML) tools hold promise in outcome prediction and assisting clinicians decision making for patients with acute intracerebral haemorrhage (ICH)

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On the other hand, preclinical studies and clinical trials highlight the potent anti-inflammatory effects of TB-500 in various models of organ and tissue injury, including in the skin, eye cornea, liver, and central nervous system [34, 35, 38, 39]

Can Poppy Seeds Cause a Positive Drug Test

doi: 10.1097/IMNA-D-24-00002