Paper Info
Title
Data integration of electronic health records using artificial neural networks
Abstract
This paper presents a system that uses cloud computing to deliver a cost effective clinical care to patients. The central component of the proposal is an electronic health record system that acts as a patient centric model, enabling health care providers to access complete patient records from any location anytime. A hybrid cloud computing model is proposed to connect all health care facilities together at a national scale. However, due to the heterogeneity of clinical database schemas, a novel technique is needed for solving the problem of data heterogeneity such that all health care providers are capable of sharing electronic health records easily. In this paper, a semi-automated classification technique using Artificial Neural Networks is adopted to solve the problem of data integration. To prove the potential of the model, an experiment was carried out and promising results were achieved.
Year
Venue
Keywords
2012
London
cloud computing,data integration,health care,medical information systems,neural nets,pattern classification,peer-to-peer computing,artificial neural networks,clinical database schemas,cost effective clinical care,data heterogeneity,data integration,electronic health record sharing,electronic health record system,health care facilities,health care providers,hybrid cloud computing model,patient centric model,semiautomated classification technique
DocType
ISSN
ISBN
Conference
2164-7046
978-1-4673-5325-0
Citations 
PageRank 
References 
2
0.39
0
Authors
4
Name
Order
Citations
PageRank
Omniyah Gul120.39
Mahmoud Al-qutayri215736.47
Quang Hieu Vu354224.63
Chan Yeob Yeun417025.61