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A Cloud Computing Based Platform for...

Guo, Yunyong.

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A Cloud Computing Based Platform for Geographically Distributed Health Data Mining.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Cloud Computing Based Platform for Geographically Distributed Health Data Mining./
Author:	Guo, Yunyong.
Description:	98 p.
Notes:	Source: Masters Abstracts International, Volume: 52-06.
Contained By:	Masters Abstracts International52-06(E).
Subject:	Health care management. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MS26422
ISBN:	9780499264220

A Cloud Computing Based Platform for Geographically Distributed Health Data Mining.
Guo, Yunyong.

A Cloud Computing Based Platform for Geographically Distributed Health Data Mining. - 98 p.

Source: Masters Abstracts International, Volume: 52-06.

Thesis (M.Sc.)--University of Victoria (Canada), 2013.

With cloud computing emerging in recent years, more and more interest has been sparked from a variety of institutions, organizations and individual users, as they intend to take advantage of web applications to share a huge amount of public and private data and information in a more affordable way and using a reliable IT architecture. In the area of healthcare, medical and health information systems based on cloud computing are desired, in order to realize the sharing of medical data and health information, coordination of clinical service, along with effective and cost-contained clinical information system infrastructure via the implementation of a distributed and highlyintegrated platform. The objective of this study is to discuss the challenges of adopting cloud computing for collaborative health research information management and provide recommendations to deal with corresponding challenges. More specially, the study will propose a cloud computing based platform according to recommendations. The platform can be used to bring together health informatics researchers from the different geographical locations to share medical data for research purposes, for instance, data mining used for improving liver cancer early detection and treatment. Finding from a literature review will be discussed to highlight challenges of applying cloud computing in a wide range of areas, and recommendations will be paired with each challenge. A proof of concept prototype research methodology will be employed to illustrate the proposed cross national cloud computing model for geographically distributed health data mining applied to a health informatics research.

ISBN: 9780499264220Subjects--Topical Terms:

2122906
Health care management.

A Cloud Computing Based Platform for Geographically Distributed Health Data Mining.
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100 1 $a Guo, Yunyong. $3 3179233
245 1 2 $a A Cloud Computing Based Platform for Geographically Distributed Health Data Mining.
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500 $a Source: Masters Abstracts International, Volume: 52-06.
500 $a Adviser: Alex Kuo.
502 $a Thesis (M.Sc.)--University of Victoria (Canada), 2013.
520 $a With cloud computing emerging in recent years, more and more interest has been sparked from a variety of institutions, organizations and individual users, as they intend to take advantage of web applications to share a huge amount of public and private data and information in a more affordable way and using a reliable IT architecture. In the area of healthcare, medical and health information systems based on cloud computing are desired, in order to realize the sharing of medical data and health information, coordination of clinical service, along with effective and cost-contained clinical information system infrastructure via the implementation of a distributed and highlyintegrated platform. The objective of this study is to discuss the challenges of adopting cloud computing for collaborative health research information management and provide recommendations to deal with corresponding challenges. More specially, the study will propose a cloud computing based platform according to recommendations. The platform can be used to bring together health informatics researchers from the different geographical locations to share medical data for research purposes, for instance, data mining used for improving liver cancer early detection and treatment. Finding from a literature review will be discussed to highlight challenges of applying cloud computing in a wide range of areas, and recommendations will be paired with each challenge. A proof of concept prototype research methodology will be employed to illustrate the proposed cross national cloud computing model for geographically distributed health data mining applied to a health informatics research.
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