Introduction Prospective clinical evaluations of decision support tools for the ICU are almost
non-existent. We sought to test whether a novel clinical decision support tool called ViSIG …

Objectives: Risk adjustment algorithms for ICU mortality are necessary for measuring and
improving ICU performance. Existing risk adjustment algorithms are not widely adopted. Key …

The aim of this study was to quantify the impact of ProCCESs AWARE, Ambient Clinical
Analytics, Rochester, MN, a novel acute care electronic medical record interface, on a range …

Modern Intensive Care Units (ICUs) provide continuous monitoring of critically ill patients
susceptible to many complications affecting morbidity and mortality. ICU settings require a …

Background Artificial intelligence–based clinical decision support (AI-CDS) tools have great
potential to benefit intensive care unit (ICU) patients and physicians. There is a gap between …

Improved ICU prognostication, enabled by advanced ML/AI methods, offer a promising
approach to inform difficult and urgent decisions under uncertainty. However, critical …

The high availability of clinical data and a heterogeneous and complex patient population
makes Intensive Care Units (ICUs) environments opportune for developing a system that …

Purpose Mortality risk prediction helps clinicians make better decisions in patient healthcare.
However, existing severity scoring systems or algorithms used in intensive care units (ICUs) …

OBJECTIVES: Hospital early warning systems that use machine learning (ML) to predict
clinical deterioration are increasingly being used to aid clinical decision-making. However, it …

Objectives: Unexpected ICU readmission is associated with longer length of stay and
increased mortality. To prevent ICU readmission and death after ICU discharge, our team of …