Abstract Machine learning is one of the essential and effective tools in analyzing highly
complex medical data. With vast amounts of medical data being generated, there is an …

Background Prognosticating the course of diseases to inform decision-making is a key
component of intensive care medicine. For several applications in medicine, new methods …

The purpose of this study was to assess the feasibility of machine learning (ML) in predicting
the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease …

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 …

Background The increasing development of artificial intelligence (AI) systems in medicine
driven by researchers and entrepreneurs goes along with enormous expectations for …

Many studies have been published on a variety of clinical applications of artificial
intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review …

Background Modern clinical care in intensive care units is full of rich data, and machine
learning has great potential to support clinical decision-making. The development of …

Background Despite wide use of severity scoring systems for case-mix determination and
benchmarking in the intensive care unit (ICU), the possibility of scoring bias across …

In the domain of using DL-based methods in medical and healthcare prediction systems, the
utilization of state-of-the-art deep learning (DL) methodologies assumes paramount …

The demographic shift, together with financial constraint, justify a re-evaluation of the
trajectory of care of very old critically ill patients (VIP), defined as older than 80 years. We …