Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach
Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square) scanning windows to discover diseas...
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| Main Authors: | , , , , |
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| Format: | Article |
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Page Press Publications
2017
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033239575&doi=10.4081%2fgh.2017.567&partnerID=40&md5=5948a5c8185bd6ddff13a31452df31ba http://eprints.utp.edu.my/19820/ |
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