DocumentCode
1375541
Title
AI for Global Disease Surveillance
Author
Hsinchun Chen ; Zeng, Deze
Author_Institution
Univ. of Arizona, Tucson, AZ, USA
Volume
24
Issue
6
fYear
2009
Firstpage
66
Lastpage
82
Abstract
Disease surveillance has been practiced for decades and continues to be an indispensable approach for detecting emerging disease outbreaks and epidemics. Early knowledge of a disease outbreak plays an important role in improving response effectiveness. In this article we presents the application of AI for the global disease surveillance systems. This also provides in depth survey that analyzes and evaluates existing syndromic surveillance system and related outbreak modelling and detection work under a unified framework. Many intelligent global disease surveillance systems have begun to emerge. To illustrate, we present the following study.
Keywords
artificial intelligence; diseases; medical computing; surveillance; AI; artificial intelligence; disease detection; intelligent global disease surveillance systems; syndromic surveillance system; Artificial intelligence; Asia; Bioterrorism; Collaborative work; Diseases; Hurricanes; Laboratories; Monitoring; Surveillance; Time series analysis; Controversies; Trends & bioterrorism; disease surveillance; epidemic monitoring and control; global data sharing; healthcare; literature mining; spatial-contact networks; syndromic surveillance;
fLanguage
English
Journal_Title
Intelligent Systems, IEEE
Publisher
ieee
ISSN
1541-1672
Type
jour
DOI
10.1109/MIS.2009.126
Filename
5372205
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