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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
2007-8-8
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pubmed:abstractText |
Recent adaptations of the spatial scan approach to detecting disease clusters have addressed the problem of finding clusters that occur in non-compact and non-circular shapes--such as along roads or river networks. Some of these approaches may have difficulty defining cluster boundaries precisely, and tend to over-fit data with very irregular (and implausible) clusters shapes.
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
1476-072X
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
6
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
28
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pubmed:dateRevised |
2010-9-15
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pubmed:meshHeading |
pubmed-meshheading:17615077-Canada,
pubmed-meshheading:17615077-Cluster Analysis,
pubmed-meshheading:17615077-Data Interpretation, Statistical,
pubmed-meshheading:17615077-Disease Outbreaks,
pubmed-meshheading:17615077-Female,
pubmed-meshheading:17615077-Humans,
pubmed-meshheading:17615077-Male,
pubmed-meshheading:17615077-Models, Statistical,
pubmed-meshheading:17615077-Sensitivity and Specificity
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pubmed:year |
2007
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pubmed:articleTitle |
Adaptations for finding irregularly shaped disease clusters.
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pubmed:affiliation |
School of Geography and Earth Sciences, McMaster University, Hamilton, Canada. niwiyi@gmail.com
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pubmed:publicationType |
Journal Article,
Review,
Research Support, Non-U.S. Gov't
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