Reviewing patients who return to the emergency department (ED) within 72 h (ie, bounce-
back) is a standard quality assurance procedure used to identify correctable system-and …

Overcrowding in emergency department (ED) causes lengthy waiting times, reduces
adequate emergency care and increases rate of mortality. Accurate prediction of daily ED …

Since early identification of potential critical patients in the Emergency Department (ED) can
lower mortality and morbidity, this study seeks to develop a machine learning model capable …

Background Emergency department (ED) overcrowding has been a serious issue and
demands effective clinical decision-making of patient disposition. In previous studies …

Hospital readmission shortly after discharge is threatening to plague the quality of inpatient
care. Readmission is a severe episode that leads to increased medical care costs. Federal …

Overcrowding is a serious issue that Emergency Departments (EDs) must deal with, since it
is leading to longer delays and greater patients' dissatisfaction, which are directly connected …

Background Among patients who are discharged from the Emergency Department (ED),
about 3% return within 30 days. Revisits can be related to the nature of the disease, medical …

Abstract Electronic Healthcare Records (EHRs) have the potential to improve healthcare
quality and to decrease costs by providing quality metrics, discovering actionable insights …

Early detection of heart complications is highly effective in treating patients with
cardiovascular diseases. Various machine learning methods have previously been used for …

With the increasing availability of Electronic Health Records (EHRs) and advances in deep
learning techniques, developing deep predictive models that use EHR data to solve …