16469531

Source:http://linkedlifedata.com/resource/pubmed/id/16469531

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0042029, umls-concept:C0242406, umls-concept:C1517503, umls-concept:C1527178, umls-concept:C1705938, umls-concept:C2004457, umls-concept:C2698872
pubmed:issue	4
pubmed:dateCreated	2007-3-5
pubmed:abstractText	Among women who present with urinary complaints, only 50% are found to have urinary tract infection. Individual urinary symptoms and urinalysis are not sufficiently accurate to discriminate those with and without the diagnosis.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/9711057
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Apr
pubmed:issn	1386-5056
pubmed:author	pubmed-author:CanarisGay JGJ, pubmed-author:FlachStephen DSD, pubmed-author:GerberBen SBS, pubmed-author:HeckerlingPaul SPS, pubmed-author:TapeThomas GTG, pubmed-author:WigtonRobert SRS
pubmed:issnType	Print
pubmed:volume	76
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	289-96
pubmed:meshHeading	pubmed-meshheading:16469531-Adult, pubmed-meshheading:16469531-Aged, pubmed-meshheading:16469531-Aged, 80 and over, pubmed-meshheading:16469531-Algorithms, pubmed-meshheading:16469531-Female, pubmed-meshheading:16469531-Forecasting, pubmed-meshheading:16469531-Humans, pubmed-meshheading:16469531-Middle Aged, pubmed-meshheading:16469531-Nebraska, pubmed-meshheading:16469531-Neural Networks (Computer), pubmed-meshheading:16469531-Urinary Tract Infections
pubmed:year	2007
pubmed:articleTitle	Predictors of urinary tract infection based on artificial neural networks and genetic algorithms.
pubmed:affiliation	Department of Medicine, University of Illinois at Chicago, IL 60612, USA. pshecker@uic.edu
pubmed:publicationType	Journal Article