Reference health
A Comparison of Time-Series Predictions for Healthcare Emergency Department Indicators and the Impact of COVID-19
15/15 checkable references clean · checked 2026-07-25
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
8 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 15 checked references that resolve
resolves10.1186/s12913-017-2407-9
Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models
resolves10.1109/ICITEED.2013.6676239
SARIMA (Seasonal ARIMA) implementation on time series to forecast the number of Malaria incidence
resolves10.1186/1471-227X-9-1
Forecasting daily attendances at an emergency department to aid resource planning
resolves10.1016/j.jbi.2008.05.003
A multivariate time series approach to modeling and forecasting demand in the emergency department
resolves10.1016/j.jbi.2015.06.022
A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia
resolves10.1109/JBHI.2015.2511820
Time-Series Approaches for Forecasting the Number of Hospital Daily Discharged Inpatients
resolves10.1002/(SICI)1097-0258(19970930)16:18<2117::AID-SIM649>3.0.CO;2-E
Ten-year follow-up of ARIMA forecasts of attendances at accident and emergency departments in the Trent region
resolves10.1016/j.eswa.2019.06.018
A Recursive General Regression Neural Network (R-GRNN) Oracle for classification problems
resolves10.3390/w12051500
Comparative Analysis of Recurrent Neural Network Architectures for Reservoir Inflow Forecasting
resolves10.1007/s10729-006-9006-3
The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta
resolves10.1001/jamanetworkopen.2018.4087
Assessment of Time-Series Machine Learning Methods for Forecasting Hospital Discharge Volume
resolves10.1109/SSCI.2018.8628909
Evolving General Regression Neural Networks using Limited Incremental Evolution for Data-Driven Modeling of Non-linear Dynamic Systems
The 8 references without a DOI — listed, not checked
no DOI — not checkedForecasting at Scale
no DOI — not checkedBox, G.E.P., and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control, University of Michigan, Holden-Day. [2nd ed.].
no DOI — not checkedVandaele, W. (1983). Applied Time Series and Box-Jenkins Models, Academic Press, Inc.. [2nd ed.].
no DOI — not checkedSpecht, D.F. (1995). Probabilistic Neural Networks and General Regression Neural Networks, Palo Alto.
no DOI — not checkedFisher, E., O’dowd, N.C., Dorning, H., Keeble, E., and Kossarova, L. (2018, February 19). Quality at a Cost. Available online: http://www.qualitywatch.org.uk/sites/files/qualitywatch/field/field_document/QWannualstatement2016%28final%29WEB.pdf.
no DOI — not checkedStephens, M., Cross, S., and Luckwell, G. (2020, October 31). Coronavirus and the Impact on Output in the UK Economy. Office for National Statistics, Available online: https://www.ons.gov.uk/economy/grossdomesticproductgdp/articles/coronavirusandtheimpactonoutputintheukeconomy/april2020.
no DOI — not checkedThorlby, R., Tinson, A., and Kraindler, J. (2020, October 31). COVID-19: Five Dimensions of Impact|The Health Foundation. No. April. Available online: https://www.health.org.uk/news-and-comment/blogs/covid-19-five-dimensions-of-impact.
no DOI — not checkedKrollner, B., Vanstone, B., and Finnie, G. (2010, January 28–30). Financial time series forecasting with machine learning techniques: A survey. Proceedings of the 8th European Symposium on Artificial Neural Networks, ESANN 2010, Bruges, Belgium.
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