Medical applications of machine learning (ML) have experienced a surge in popularity in
recent years. The intensive care unit (ICU) is a natural habitat for ML given the abundance of …

In recent years, extensive resources are dedicated to the development of machine learning
(ML) based clinical prediction models for intensive care unit (ICU) patients. These models …

A large volume of research has considered the creation of predictive models for clinical data;
however, much existing literature reports results using only a single source of data. In this …

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

Progress of machine learning in critical care has been difficult to track, in part due to
absence of public benchmarks. Other fields of research (such as computer vision and …

Progress of machine learning in critical care has been difficult to track, in part due to
absence of public benchmarks. Other fields of research (such as vision and NLP) have …

Clinical practice in intensive care units (ICUs) requires early warnings when a patient's
condition is about to deteriorate so that preventive measures can be undertaken. To this …

In 1986, the world was shaken by the Challenger space shuttle disaster. In the years that
followed, the American National Aeronautics and Space Administration (NASA) called for a …

Objective The growing availability of rich clinical data such as patients' electronic health
records provide great opportunities to address a broad range of real-world questions in …

Prediction of mortality in intensive care unit (ICU) patients is an important task in critical care
medicine. Prior work in creating mortality risk models falls into two major categories: domain …