Predicting hospital emergency department visits with deep learning approaches
Overcrowding in emergency department (ED) causes lengthy waiting times, reduces
adequate emergency care and increases rate of mortality. Accurate prediction of daily ED …
adequate emergency care and increases rate of mortality. Accurate prediction of daily ED …
A deep learning architecture for forecasting daily emergency department visits with acuity levels
Abstract Accurate forecasting of Emergency Department (ED) visits is important for decision-
making purposes in hospitals. It helps to form tactical and operational level plans, which …
making purposes in hospitals. It helps to form tactical and operational level plans, which …
Hospital admission location prediction via deep interpretable networks for the year-round improvement of emergency patient care
Objective: This paper presents a deep learning method of predicting where in a hospital
emergency patients will be admitted after being triaged in the Emergency Department (ED) …
emergency patients will be admitted after being triaged in the Emergency Department (ED) …
[PDF][PDF] Predicting patient waiting time in the queue system using deep learning algorithms in the emergency room
H Hijry, R Olawoyin - International Journal of Industrial Engineering, 2021 - ieomsociety.org
Many hospitals consider the length of time waiting in queue to be a measure of emergency
room (ER) overcrowding. Long waiting times plague many ER departments, hindering the …
room (ER) overcrowding. Long waiting times plague many ER departments, hindering the …
An LSTM-based deep learning approach with application to predicting hospital emergency department admissions
F Kadri, M Baraoui, I Nouaouri - 2019 International Conference …, 2019 - ieeexplore.ieee.org
Since the need for medical cares has significantly increased all over the last years, the
efficient management of patient flow becomes a core element for hospitals and particularly …
efficient management of patient flow becomes a core element for hospitals and particularly …
Using long short-term memory (LSTM) neural networks to predict emergency department wait time
N Cheng, A Kuo - The Importance of Health Informatics in Public …, 2020 - ebooks.iospress.nl
Emergency Department (ED) overcrowding is a major global healthcare issue. Many
research studies have been conducted to predict ED wait time using various machine …
research studies have been conducted to predict ED wait time using various machine …
[HTML][HTML] Towards accurate prediction of patient length of stay at emergency department: a GAN-driven deep learning framework
Recently, the hospital systems face a high influx of patients generated by several events,
such as seasonal flows or health crises related to epidemics (eg, COVID'19). Despite the …
such as seasonal flows or health crises related to epidemics (eg, COVID'19). Despite the …
Patient visit forecasting in an emergency department using a deep neural network approach
Purpose This study aims to investigate the factors affecting daily demand in an emergency
department (ED) and to provide a forecasting tool in a public hospital for horizons of up to …
department (ED) and to provide a forecasting tool in a public hospital for horizons of up to …
Forecasting emergency department overcrowding: A deep learning framework
As the demand for medical cares has considerably expanded, the issue of managing patient
flow in hospitals and especially in emergency departments (EDs) is certainly a key issue to …
flow in hospitals and especially in emergency departments (EDs) is certainly a key issue to …
[HTML][HTML] A deep learning approach for predicting early bounce-backs to the emergency departments
B Davazdahemami, P Peng, D Delen - Healthcare Analytics, 2022 - Elsevier
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 …
back) is a standard quality assurance procedure used to identify correctable system-and …