Source:http://linkedlifedata.com/resource/pubmed/id/16962295
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
3
|
| pubmed:dateCreated |
2006-11-20
|
| pubmed:abstractText |
Patients with suspicion of acute coronary syndrome (ACS) are difficult to diagnose and they represent a very heterogeneous group. Some require immediate treatment while others, with only minor disorders, may be sent home. Detecting ACS patients using a machine learning approach would be advantageous in many situations.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Nov
|
| pubmed:issn |
0933-3657
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
38
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
305-18
|
| pubmed:meshHeading |
pubmed-meshheading:16962295-Acute Disease,
pubmed-meshheading:16962295-Aged,
pubmed-meshheading:16962295-Calibration,
pubmed-meshheading:16962295-Coronary Disease,
pubmed-meshheading:16962295-Emergency Service, Hospital,
pubmed-meshheading:16962295-Female,
pubmed-meshheading:16962295-Humans,
pubmed-meshheading:16962295-Logistic Models,
pubmed-meshheading:16962295-Male,
pubmed-meshheading:16962295-Middle Aged,
pubmed-meshheading:16962295-Neural Networks (Computer),
pubmed-meshheading:16962295-Risk Factors
|
| pubmed:year |
2006
|
| pubmed:articleTitle |
Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room.
|
| pubmed:affiliation |
Department of Theoretical Physics, Lund University, Sölvegatan 14A, SE-22362 Lund, Sweden. michael@thep.lu.se
|
| pubmed:publicationType |
Journal Article,
Comparative Study,
Research Support, Non-U.S. Gov't,
Evaluation Studies
|