Linked Life Data

11377148

Source:http://linkedlifedata.com/resource/pubmed/id/11377148

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2001-5-29
pubmed:abstractText
This paper describes the analysis of a database of diabetic patients' clinical records and death certificates. The objective of the study was to find rules that describe associations between observations made of patients at their first visit to the hospital and early mortality.Pre-processing was carried out and a knowledge discovery in databases (KDD) package, developed by the Lanner Group and the University of East Anglia, was used for rule induction using simulated annealing.The most significant discovered rules describe an association that was not generally known or accepted by the medical community, however, recent independent studies confirm their validity.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0933-3657
pubmed:author
pubmed:issnType
Print
pubmed:volume
22
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
215-31
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Data mining for indicators of early mortality in a database of clinical records.
pubmed:affiliation
School of Information Systems, University of East Anglia, NR4 7TJ, Norwich, UK. graeme.richards@uea.ac.uk
pubmed:publicationType
Journal Article