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A Novel Disease Outbreak Prediction Model for Compact Spatial-Temporal Environments
Lao, Kam Kin1; Deb, Suash2; Thampi, Sabu M.3; Fong, Simon1
2014
Conference NameInternational Symposium on Signal Processing and Intelligent Recognition Systems, SIRS 2014
Source PublicationAdvances in Intelligent Systems and Computing
Volume264
Pages439-450
Conference DateMAR 13-15, 2014
Conference PlaceTrivandrum, India
Author of SourceSpringer Verlag
PublisherSPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Abstract

One of the popular research areas in clinical decision supporting system (CDSS) is Spatial and temporal (ST) data mining. The basic concept of ST concerns about two combined dimensions of analyzing: time and space. For prediction of disease outbreak, we attempt to locate any potential uninfected by the predicted virus prevalence. A popular ST-clustering software called "SaTScan" works by predicting the next likely infested areas by considering the history records of infested zones and the radius of the zone. However, it is argued that using radius as a spatial measure suits large and perhaps evenly populated area. In urban city, the population density is relatively high and uneven. In this paper, we present a novel algorithm, by following the concept of SaTScan, but in consideration of spatial information in relation to local populations and full demographic information in proximity (e.g. that of a street or a cluster of buildings). This higher resolution of ST data mining has an advantage of precision and applicability in some very compact urban cities. For proving the concept a computer simulation model is presented that is based on empirical but anonymized and processed data. 

DOIhttps://doi.org/10.1007/978-3-319-04960-1_39
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS IDWOS:000391155100039
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.University of Macau, Taipa, Macau SAR, China;
2.Cambridge Institute of Technology, Ranchi, India;
3.Indian Institute of Information Technology and Management, Kerala, India
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Lao, Kam Kin,Deb, Suash,Thampi, Sabu M.,et al. A Novel Disease Outbreak Prediction Model for Compact Spatial-Temporal Environments[C]//Springer Verlag:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY,2014:439-450.
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