Switch to
| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
5
|
| pubmed:dateCreated |
1994-6-16
|
| pubmed:abstractText |
Neural networks are a group of computer-based pattern recognition methods that have recently been applied to clinical diagnosis and classification. In this study, we applied one type of neural network, the backpropagation network, to the diagnostic classification of giant cell arteritis (GCA).
|
| pubmed:grant | |
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
AIM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
May
|
| pubmed:issn |
0004-3591
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
37
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
760-70
|
| pubmed:dateRevised |
2010-3-24
|
| pubmed:meshHeading |
pubmed-meshheading:8185705-Diagnosis, Computer-Assisted,
pubmed-meshheading:8185705-Giant Cell Arteritis,
pubmed-meshheading:8185705-Humans,
pubmed-meshheading:8185705-Middle Aged,
pubmed-meshheading:8185705-Neural Networks (Computer),
pubmed-meshheading:8185705-ROC Curve,
pubmed-meshheading:8185705-Sensitivity and Specificity
|
| pubmed:year |
1994
|
| pubmed:articleTitle |
Application of neural networks to the classification of giant cell arteritis.
|
| pubmed:affiliation |
University of Washington, Department of Laboratory Medicine, Seattle 98195.
|
| pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.
|