Source:http://linkedlifedata.com/resource/pubmed/id/19608995
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
9
|
| pubmed:dateCreated |
2009-8-27
|
| pubmed:abstractText |
It has been hypothesized that algorithms predicting the final outcome in acute ischemic stroke may provide future tools for identifying salvageable tissue and hence guide individualized therapy. We developed means of quantifying predictive model performance to identify model training strategies that optimize performance and reduce bias in predicted lesion volumes.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Sep
|
| pubmed:issn |
1524-4628
|
| pubmed:author | |
| pubmed:issnType |
Electronic
|
| pubmed:volume |
40
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
3006-11
|
| pubmed:meshHeading |
pubmed-meshheading:19608995-Aged,
pubmed-meshheading:19608995-Algorithms,
pubmed-meshheading:19608995-Brain Infarction,
pubmed-meshheading:19608995-Female,
pubmed-meshheading:19608995-Humans,
pubmed-meshheading:19608995-Magnetic Resonance Imaging,
pubmed-meshheading:19608995-Male,
pubmed-meshheading:19608995-Middle Aged,
pubmed-meshheading:19608995-Models, Biological,
pubmed-meshheading:19608995-Predictive Value of Tests,
pubmed-meshheading:19608995-Stroke
|
| pubmed:year |
2009
|
| pubmed:articleTitle |
Predicting tissue outcome from acute stroke magnetic resonance imaging: improving model performance by optimal sampling of training data.
|
| pubmed:affiliation |
Department of Neuroradiology, Center of Functionally Integrative Neuroscience, Arhus University Hospital, Arhus, Denmark. krissa@pet.auh.dk
|
| pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|