An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments

M Gul, E Celik - Health Systems, 2020 - Taylor & Francis
Emergency departments (EDs) provide medical treatment for a broad spectrum of illnesses
and injuries to patients who arrive at all hours of the day. The quality and efficient delivery of …

Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study

VK Sudarshan, M Brabrand, TM Range… - Computers in Biology and …, 2021 - Elsevier
The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is
a significant reason of ED crowding in hospitals worldwide. Timely forecast of patients …

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models

L Luo, L Luo, X Zhang, X He - BMC health services research, 2017 - Springer
Background Accurate forecasting of hospital outpatient visits is beneficial for the reasonable
planning and allocation of healthcare resource to meet the medical demands. In terms of the …

[HTML][HTML] A systematic review of the modelling of patient arrivals in emergency departments

S Jiang, Q Liu, B Ding - Quantitative Imaging in Medicine and …, 2023 - ncbi.nlm.nih.gov
Background Accident and Emergency Department (AED) is the frontline of providing
emergency care in a hospital and research focusing on improving decision-makings and …

Forecasting emergency department overcrowding: A deep learning framework

F Harrou, A Dairi, F Kadri, Y Sun - Chaos, Solitons & Fractals, 2020 - Elsevier
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 …

Towards accurate prediction of patient length of stay at emergency department: a GAN-driven deep learning framework

F Kadri, A Dairi, F Harrou, Y Sun - Journal of Ambient Intelligence and …, 2023 - Springer
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 …

Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: a case study

M Ortiz-Barrios, S Arias-Fonseca, A Ishizaka… - Journal of business …, 2023 - Elsevier
The Covid-19 pandemic has pushed the Intensive Care Units (ICUs) into significant
operational disruptions. The rapid evolution of this disease, the bed capacity constraints, the …

A forecasting framework for the Indian healthcare sector index

J Sen - International Journal of Business Forecasting and …, 2022 - inderscienceonline.com
Forecasting of future stock prices is a complex and challenging research problem due to the
random variations that the time series of these variables exhibit. In this work, we study the …

Improved principal component analysis for anomaly detection: Application to an emergency department

F Harrou, F Kadri, S Chaabane, C Tahon… - Computers & Industrial …, 2015 - Elsevier
Monitoring of production systems, such as those in hospitals, is primordial for ensuring the
best management and maintenance desired product quality. Detection of emergent …

Seasonal ARMA-based SPC charts for anomaly detection: Application to emergency department systems

F Kadri, F Harrou, S Chaabane, Y Sun, C Tahon - Neurocomputing, 2016 - Elsevier
Monitoring complex production systems is primordial to ensure management, reliability and
safety as well as maintaining the desired product quality. Early detection of emergent …