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This study explores the use of Behavioural Artificial Intelligence Technology (BAIT) to identify objective variables for retrospective sepsis surveillance. Experts evaluated hypothetical patient scenarios to determine the presence of sepsis, with key variables being temperature, CRP, and systolic blood pressure, achieving model accuracy of 74-75%. The findings highlight the importance of inflammatory parameters in identifying suspected infections and suggest that BAIT can improve sepsis surveillance accurac

Author

tanushree110803

Language

EN