Background Advances in machine learning (ML) provide great opportunities in the
prediction of hospital readmission. This review synthesizes the literature on ML methods and …

Mining health data can lead to faster medical decisions, improvement in the quality of
treatment, disease prevention, and reduced cost, and it drives innovative solutions within the …

Background Despite apparent promise and the availability of numerous examples in the
literature, machine learning models are rarely used in practice in ICU units. This mismatch …

Background: We determined the impact of data volume and diversity and training conditions
on recurrent neural network methods compared with traditional machine learning methods …

Context: Determining which patients are ready for discharge from an Intensive Care Unit
(ICU) presents a huge challenge, as ICU readmissions are associated with several negative …

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 …

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

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 …

Electronic Health Record (EHR) systems provide critical, rich and valuable information at
high frequency. One of the most exciting applications of EHR data is in developing a real …

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