
In the critical care setting, a study compares the efficacy of machine learning (ML) alerts, telemedicine system (TS) alerts, and biomedical monitor (BM) alarms in predicting episodes of intubation or vasopressor administration. ML notifications demonstrate superior accuracy, precision, and a 50-fold lower alarm burden compared to TS alerts. Internal and external validation, including a COVID-19 cohort, support ML's consistent performance. ML alerts offer a significant advancement, providing more proactive care with minimal disruption to clinician workflows compared to TS and BM alerts.
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