Background Despite the interest in machine learning (ML) algorithms for analyzing real-
world data (RWD) in healthcare, the use of ML in predicting time-to-event data, a common …

Hospital readmission is one of the challenges that force an extra pressure and financial
burden on healthcare and causes a significant waste of medical resources. However, some …

Abstract Background Intensive Care Unit (ICU) readmissions represent both a health risk for
patients, with increased mortality rates and overall health deterioration, and a financial …

Predicting 30-day hospital readmission is a core research task in the development of
personalized healthcare. However, the imbalanced class distribution and the heterogeneity …

With the emergence of big data and the interest in deriving valuable insights from ever‐
growing and ever‐changing streams of data, machine learning has appeared as an effective …

An ICU is a critical care unit that provides advanced medical support and continuous
monitoring for patients with severe illnesses or injuries. Predicting the mortality rate of ICU …

OBJECTIVES: To evaluate the methodologic rigor and predictive performance of models
predicting ICU readmission; to understand the characteristics of ideal prediction models; and …

Objective To review and evaluate existing risk assessment tools for intensive care
unitreadmission. Methods Nine electronic databases (Medline, CINAHL, Web of Science …

ICU readmission is usually associated with an increased number of hospital death.
Predicting readmission helps to reduce such risks by avoiding early discharge, providing …

Intensive care unit (ICU) readmissions are associated with mortality and poor outcomes. To
improve discharge decisions, machine learning (ML) could help to identify patients at risk of …