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Common causes of death in hospitals, such as sepsis and respiratory failure, are treatable and benefit from early intervention. Machine learning algorithms or early warning scores can be used for early identification and recognition to potentially help accelerate interventions and limit morbidity and mortality. This Concise Critical Appraisal explores an article published in Critical Care Medicine that looked at the impact of one of these early warning scores—electronic cardiac arrest risk triage (eCART)—on mortality for elevated-risk adult inpatients.