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Title: How can AI and ML disrupt critical care? Authors:  Romain Pirracchio - UCSF (United States) [presenting]
Abstract: The importance of critical care has been highlighted during the Covid-19 pandemic. It has also highlighted the fact that ICU resources are limited and should be used wisely. Ever since its creation in the mid-1900s, critical care has typically been a curative healthcare service. Indeed, patients are admitted to the ICU if they present organ dysfunctions that can only be treated in the ICU environment. Although supportive care is much needed in the most severe patients, an alternative approach where patients at risk of deterioration are identified early could help prevent organ dysfunction from happening and potentially improve the outcome, and also help better identify the patients who need to be treated in an ICU environment. Recent developments in predictive analytics may promote the much-needed transition from a purely curative to more of a preventative paradigm for ICU care delivery.