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Description
What we found: By experimentally manipulating juvenile hormone (JH) levels in nearly 500 earwig mothers after oviposition (i.e

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Wormers are not

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
Retrieved from Pawlak, R., Lester, S

Symptoms can range from mild skin irritation to severe reactions , including anaphylaxis in rare cases
