Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2002-11-11
pubmed:abstractText
Accurate prediction of the effect of atmospheric changes, including pollutants, on emergency department (ED) visits for respiratory symptoms would be useful, but has proven difficult. The main difficulty is the limitation of the classical linear models and logistic regression with multiple variables to handle the multifactorial effect.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0012-3692
pubmed:author
pubmed:issnType
Print
pubmed:volume
122
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1627-32
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Prediction of emergency department visits for respiratory symptoms using an artificial neural network.
pubmed:affiliation
Barzilai Medical Center, Ashkelon, Israel. haim_76407@yahoo.com
pubmed:publicationType
Journal Article