This article is one of ten reviews selected from the Annual Update in Intensive Care and
Emergency Medicine 2020. Other selected articles can be found online at https://www …

Abstract Background Intensive care units (ICUs) face financial, bed management, and
staffing constraints. Detailed data covering all aspects of patients' journeys into and through …

Abstract Machine learning can predict outcomes and determine variables contributing to
precise prediction, and can thus classify patients with different risk factors of outcomes. This …

Background and aim: Artificial intelligence was born to allow computers to learn and control
their environment, trying to imitate the human brain structure by simulating its biological …

A model that accurately predicts, at the time of admission, the Length of Stay (LOS) for
hospitalized patients could be an effective tool for healthcare providers. It could enable early …

Background Risk stratification plays a central role in anesthetic evaluation. The use of Big
Data and machine learning (ML) offers considerable advantages for collection and …

There is a vast development of artificial intelligence (AI) in recent years. Computational
technology, digitized data collection and enormous advancement in this field have allowed …

Robust and rabid mortality prediction is crucial in intensive care units because it is
considered one of the critical steps for treating patients with serious conditions. Combining …

In 1985, development of a computer system called “Deep Thought” began at Carnegie
Mellon University with the lofty objective of develo** an autonomous system capable of …

Background Multiple organ dysfunction is a common cause of morbidity and mortality in
intensive care units (ICUs). Original development of the Sequential Organ Failure …