Source:http://linkedlifedata.com/resource/pubmed/id/16520157
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
3
|
| pubmed:dateCreated |
2006-3-7
|
| pubmed:abstractText |
To identify the best method for the prediction of postoperative mortality in individual abdominal aortic aneurysm surgery (AAA) patients by comparing statistical modelling with artificial neural networks' (ANN) and clinicians' estimates.
|
| pubmed:commentsCorrections | |
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Mar
|
| pubmed:issn |
0741-5214
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
43
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
467-473
|
| pubmed:dateRevised |
2006-11-15
|
| pubmed:meshHeading |
pubmed-meshheading:16520157-Aortic Aneurysm, Abdominal,
pubmed-meshheading:16520157-Female,
pubmed-meshheading:16520157-Humans,
pubmed-meshheading:16520157-Male,
pubmed-meshheading:16520157-Models, Statistical,
pubmed-meshheading:16520157-Neural Networks (Computer),
pubmed-meshheading:16520157-Prognosis
|
| pubmed:year |
2006
|
| pubmed:articleTitle |
Informed prognosis [corrected] after abdominal aortic aneurysm repair using predictive modeling techniques [corrected].
|
| pubmed:affiliation |
Nuffield Department of Surgery, John Radcliffe Hospital, Oxford, United Kingdom. vassilis@doctors.org.uk
|
| pubmed:publicationType |
Journal Article,
Comparative Study,
Research Support, Non-U.S. Gov't,
Multicenter Study
|