Patients in the Intensive Care Unit can deteriorate very quickly, leading to unexpected negative outcomes. There is a great need for continuous predictive modeling to identify these negative outcomes early and improve patient management and outcomes. Our continuous modeling will predict sepsis along with sepsis-related outcomes, organ failure and in-hospital mortality, using only 1 hour of data with greater precision when compared to the clinical risk scores most appropriately matched for each outcome.

Learning Objective: Learn the challenges in developing continuous predictive modelling for sepsis, organ Failure, and in-hospital mortality in the intensive care unit


Amber Kiser, University of Utah
Devin Horton, University of Utah
Karen Eilbeck, University of Utah
Samir Abdelrahman (Presenter)
University of Utah

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