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
Link To Document :
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