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 …

A two-stage stochastic integer programming approach to integrated staffing and scheduling with application to nurse management

K Kim, S Mehrotra - Operations Research, 2015 - pubsonline.informs.org
We study the problem of integrated staffing and scheduling under demand uncertainty. This
problem is formulated as a two-stage stochastic integer program with mixed-integer …

Predicting inpatient flow at a major hospital using interpretable analytics

D Bertsimas, J Pauphilet, J Stevens… - … & Service Operations …, 2022 - pubsonline.informs.org
Problem definition: Translate data from electronic health records (EHR) into accurate
predictions on patient flows and inform daily decision making at a major hospital …

Fast surrogate modeling using dimensionality reduction in model inputs and field output: Application to additive manufacturing

M Vohra, P Nath, S Mahadevan, YTT Lee - Reliability engineering & system …, 2020 - Elsevier
A novel approach to surrogate modeling motivated by recent advancements in parameter
dimension reduction is proposed. Specifically, the approach aims to speed-up surrogate …

Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the soil moisture active–passive satellite and evaluation at core validation sites

SB Kim, JJ Van Zyl, JT Johnson… - … on Geoscience and …, 2017 - ieeexplore.ieee.org
This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial
resolution using L-band dual-copolarized Soil Moisture Active-Passive (SMAP) synthetic …

Probabilistic forecasting of hourly emergency department arrivals

B Rostami-Tabar, J Browell, I Svetunkov - Health Systems, 2024 - Taylor & Francis
An accurate forecast of Emergency Department (ED) arrivals by an hour of the day is critical
to meet patients' demand. It enables planners to match ED staff to the number of arrivals …

Assessment of time-series machine learning methods for forecasting hospital discharge volume

TH McCoy, AM Pellegrini, RH Perlis - JAMA network open, 2018 - jamanetwork.com
Importance Forecasting the volume of hospital discharges has important implications for
resource allocation and represents an opportunity to improve patient safety at periods of …

Recursive neural networks in hospital bed occupancy forecasting

E Kutafina, I Bechtold, K Kabino, SM Jonas - BMC medical informatics and …, 2019 - Springer
Background Efficient planning of hospital bed usage is a necessary condition to minimize
the hospital costs. In the presented work we deal with the problem of occupancy forecasting …

Performance and cyclic heat behavior of a partially adiabatic Cased-Wellbore Compressed Air Energy Storage system

S Sarmast, RA Fraser, MB Dusseault - Journal of Energy Storage, 2021 - Elsevier
Abstract Although Compressed Air Energy Storage (CAES) is not a new technology, it has
not yet been widely adopted due to location restrictions and inefficiencies. Thermal energy …

Machine learning-based patient load prediction and IoT integrated intelligent patient transfer systems

K Mtonga, S Kumaran, C Mikeka, K Jayavel, J Nsenga - future internet, 2019 - mdpi.com
A mismatch between staffing ratios and service demand leads to overcrowding of patients in
waiting rooms of health centers. Overcrowding consequently leads to excessive patient …