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 …
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 …
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 …
[HTML][HTML] Evaluating the impact of exogenous variables for patients forecasting in an Emergency Department using Attention Neural Networks
Emergency Department overcrowding is a well-known problem. The consequences are long
waiting times for patients, reduced service quality, and the potential for increased mortality …
waiting times for patients, reduced service quality, and the potential for increased mortality …
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 …
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 …
Deep learning-based patient visits forecasting using long short term memory
HT Karsanti, I Ardiyanto… - … international conference of …, 2019 - ieeexplore.ieee.org
Predicting the number of patient visits to hospitals has been acknowledged remarkably
helpful in the decision-making related to allocating limited human and material resources of …
helpful in the decision-making related to allocating limited human and material resources of …
[HTML][HTML] Effective forecasting of key features in hospital emergency department: Hybrid deep learning-driven methods
Forecasting the different types of emergency department (ED) demands (patient flows) in
hospital systems much aids ED managers in looking into various options to appropriately …
hospital systems much aids ED managers in looking into various options to appropriately …
Rnn-based deep-learning approach to forecasting hospital system demands: application to an emergency department
F Kadri, K Abdennbi - International Journal of Data Science, 2020 - inderscienceonline.com
In recent years the management of patient flow is one of the main challenges faced by many
hospital establishments, in particular emergency departments (EDs). Increasing number of …
hospital establishments, in particular emergency departments (EDs). Increasing number of …
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 …