pubmed-article:11832297 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:11832297 | lifeskim:mentions | umls-concept:C0026339 | lld:lifeskim |
pubmed-article:11832297 | lifeskim:mentions | umls-concept:C0013546 | lld:lifeskim |
pubmed-article:11832297 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
pubmed-article:11832297 | lifeskim:mentions | umls-concept:C0582147 | lld:lifeskim |
pubmed-article:11832297 | lifeskim:mentions | umls-concept:C0336791 | lld:lifeskim |
pubmed-article:11832297 | pubmed:issue | 2 | lld:pubmed |
pubmed-article:11832297 | pubmed:dateCreated | 2002-2-8 | lld:pubmed |
pubmed-article:11832297 | pubmed:abstractText | Despite the increasing number of models to predict infection risk for a range of diseases, the assessment of their spatial limits, predictive performance and practical application are not widely undertaken. Using the example of Schistosoma haematobium in Africa, this article illustrates how ecozonation and receiver-operator characteristic analysis can help to assess the usefulness of available models objectively. | lld:pubmed |
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pubmed-article:11832297 | pubmed:language | eng | lld:pubmed |
pubmed-article:11832297 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:11832297 | pubmed:citationSubset | IM | lld:pubmed |
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pubmed-article:11832297 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:11832297 | pubmed:month | Feb | lld:pubmed |
pubmed-article:11832297 | pubmed:issn | 1471-4922 | lld:pubmed |
pubmed-article:11832297 | pubmed:author | pubmed-author:HaySimon ISI | lld:pubmed |
pubmed-article:11832297 | pubmed:author | pubmed-author:BrookerSimonS | lld:pubmed |
pubmed-article:11832297 | pubmed:author | pubmed-author:BundyDon A... | lld:pubmed |
pubmed-article:11832297 | pubmed:issnType | Print | lld:pubmed |
pubmed-article:11832297 | pubmed:volume | 18 | lld:pubmed |
pubmed-article:11832297 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:11832297 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:11832297 | pubmed:pagination | 70-4 | lld:pubmed |
pubmed-article:11832297 | pubmed:dateRevised | 2011-9-13 | lld:pubmed |
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pubmed-article:11832297 | pubmed:year | 2002 | lld:pubmed |
pubmed-article:11832297 | pubmed:articleTitle | Tools from ecology: useful for evaluating infection risk models? | lld:pubmed |
pubmed-article:11832297 | pubmed:affiliation | Dept of Infectious Disease Epidemiology, Imperial College School of Medicine, Norfolk Place, W2 1PG, London, UK. s.brooker@ic.ac.uk | lld:pubmed |
pubmed-article:11832297 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:11832297 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
pubmed-article:11832297 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
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