Linked Life Data

12675873

Source:http://linkedlifedata.com/resource/pubmed/id/12675873

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2003-4-4
pubmed:abstractText
Predicting outcomes such as end-stage renal disease (ESRD) by integration and better utilization at individual level of epidemiologic data may facilitate clinical decision-making processes.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0085-2538
pubmed:author
pubmed:issnType
Print
pubmed:volume
63
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1924-33
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Predicting end-stage renal disease: Bayesian perspective of information transfer in the clinical decision-making process at the individual level.
pubmed:affiliation
Department of Renal Medicine, Clinical Research Centre for Rare Diseases Aldo e Cele Daccò, Mario Negri Institute for Pharmacological Research, Villa Camozzi, Ranica (BG), Italy. manuelap@marionegri.it
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't