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Building cloud-based healthcare data mining services

Zhang, Peng, Hu, Shang, He, Jing, Zhang, Yanchun, Huang, Guangyan and Zhang, Jiekui 2016, Building cloud-based healthcare data mining services, in SCC 2016 : Proceedings of the 13th IEEE International Conference on Services Computing, IEEE, Piscataway, N.J., pp. 1-8, doi: 10.1109/SCC.2016.66.

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Title Building cloud-based healthcare data mining services
Author(s) Zhang, Peng
Hu, Shang
He, Jing
Zhang, Yanchun
Huang, Guangyan
Zhang, Jiekui
Conference name Services Computing. International Conference (13th : 2016 : San Francisco, California)
Conference location San Francisco, California
Conference dates 27 Jun.- 2 Jul. 2016
Title of proceedings SCC 2016 : Proceedings of the 13th IEEE International Conference on Services Computing
Editor(s) [Unknown]
Publication date 2016
Conference series IEEE International Conference on Services Computing
Start page 1
End page 8
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) cloud service
healthcare data
data mining
predictive model
FLOS
Summary The linkage between healthcare service and cloud computing techniques has drawn much attention lately. Up to the present, most works focus on IT system migration and the management of distributed healthcare data rather than taking advantage of information hidden in the data. In this paper, we propose to explore healthcare data via cloud-based healthcare data mining services. Specifically, we propose a cloud-based healthcare data mining framework for healthcare data mining service development. Under such framework, we further develop a cloud-based healthcare data mining service to predict patients future length of stay in hospital.
ISBN 9781509026289
Language eng
DOI 10.1109/SCC.2016.66
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30083661

Document type: Conference Paper
Collections: School of Information Technology
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Created: Tue, 13 Sep 2016, 09:36:50 EST

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