Importance Despite the potential of machine learning to improve multiple aspects of patient
care, barriers to clinical adoption remain. Randomized clinical trials (RCTs) are often a …

As a subfield of machine learning, reinforcement learning (RL) aims at optimizing decision
making by using interaction samples of an agent with its environment and the potentially …

The early prediction of deterioration could have an important role in supporting healthcare
professionals, as an estimated 11% of deaths in hospital follow a failure to promptly …

Sepsis is the third leading cause of death worldwide and the main cause of mortality in
hospitals,–, but the best treatment strategy remains uncertain. In particular, evidence …

Critical care patients are monitored closely through the course of their illness. As a result of
this monitoring, large amounts of data are routinely collected for these patients. Philips …

It is a widely accepted fact that almost every research or business revolves around Data.
Data from various business sectors has been growing sharply and the management of this …

With a massive influx of multimodality data, the role of data analytics in health informatics
has grown rapidly in the last decade. This has also prompted increasing interests in the …

Purpose Due to the increasing demand for intensive care unit (ICU) treatment, and to
improve quality and efficiency of care, there is a need for adequate and efficient clinical …

Background Many mortality prediction models have been developed for patients in intensive
care units (ICUs); most are based on data available at ICU admission. We investigated …

Leveraging real-world health data for machine learning tasks requires addressing many
practical challenges, such as distributed data silos, privacy concerns with creating a …