Openly accessible

Developing a neural network model to monitor and predict waiting times in the emergency department

Rezazadeh Niavarani, Mohammad 2018, Developing a neural network model to monitor and predict waiting times in the emergency department, Ph.D thesis, School of Nursing & Midwifery, Deakin University.

Attached Files
Name Description MIMEType Size Downloads
niavarani-developinganeural-2018.pdf Connect to thesis application/pdf 8.52MB 21

Title Developing a neural network model to monitor and predict waiting times in the emergency department
Author Rezazadeh Niavarani, Mohammad
Institution Deakin University
School School of Nursing & Midwifery
Faculty Faculty of Health
Degree name Ph.D
Thesis advisor Wickramasinge, NilminiORCID iD for Wickramasinge, Nilmini orcid.org/0000-0002-1314-8843
Date submitted 2018-10-04
Summary In parallel with manufacturing context, quality control toward provided services in service organisations have been growing as well including healthcare industry, but often models of healthcare service quality face challenges in measuring quality. The developed meta-algorithm and ANN models in this thesis can facilitate measuring service quality in Healthcare industry.
Language eng
Field of Research 080702 Health Informatics
Socio Economic Objective 920299 Health and Support Services not elsewhere classified
Description of original 155 p.
Copyright notice ┬ęThe author
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30115366

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 14 Abstract Views, 23 File Downloads  -  Detailed Statistics
Created: Fri, 16 Nov 2018, 10:22:18 EST by Bayne Christine

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.