A Hybrid Approach for Forecasting Patient Visits in Emergency Department-Reference-Cited by-同舟云学术

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A Hybrid Approach for Forecasting Patient Visits in Emergency Department

Published:2016-10-06 Issue:8 Volume:32 Page:2751-2759
ISSN:0748-8017
Container-title:Quality and Reliability Engineering International
language:en
Short-container-title:Qual. Reliab. Engng. Int.

Author:

Xu Qinneng¹,Tsui Kwok-Leung¹,Jiang Wei²,Guo Hainan¹

Affiliation:

1. City University of Hong Kong; Hong Kong People's Republic of China

2. Shanghai Jiao Tong University; Shanghai People's Republic of China

Funder

Research Grants Council Collaborative Research Fund

Theme-Based Research Scheme

National Natural Science Foundation of China

Program of Shanghai Subject Chief Scientist

Publisher

Wiley

Subject

Management Science and Operations Research,Safety, Risk, Reliability and Quality

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/qre.2095/fullpdf

Reference20 articles.

1. Forecasting models of emergency department crowding;Schweigler;Academic Emergency Medicine,2009

2. Daily patient flow is not surge: “management is prediction”;Davidson;Academic Emergency Medicine,2006

3. The challenge of predicting demand for emergency department services;Mccarthy;Academic Emergency Medicine,2008

4. From model to forecasting: a multicenter study in emergency departments;Wargon;Academic Emergency Medicine,2010

5. Forecasting daily emergency department visits using calendar variables and ambient temperature readings;Marcilio;Academic Emergency Medicine,2013

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1. Enhancing emergency department patient arrival forecasting: a study using feature engineering and advanced machine learning algorithms;2024-02-02

2. Forecasting patient demand at urgent care clinics using explainable machine learning;CAAI Transactions on Intelligence Technology;2023-07-11

3. Machine learning methods for predicting the admissions and hospitalisations in the emergency department of a civil and military hospital;Journal of Intelligent Information Systems;2023-07-04

4. Forecasting patient flows with pandemic induced concept drift using explainable machine learning;EPJ Data Science;2023-04-21

5. Forecasting Future Monthly Patient Volume using Deep Learning and Statistical Models;Wireless Personal Communications;2023-03-10

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