Linked Life Data

7729844

Source:http://linkedlifedata.com/resource/pubmed/id/7729844

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1995-6-1
pubmed:abstractText
Quantitative electroencephalographic (EEG) signal analysis has revealed itself as an important diagnostic tool in the last few years. Through the use of signal processing techniques, new quantitative representations of EEG data are obtained. To automate the diagnosis, a problem of supervised classification must be solved on these. Artificial Neural Networks provide an alternative to more traditional classifier systems for this task. The objective of this paper is to perform a comparison between several classifiers in a particular problem, the brain maturation prediction. The data preprocessing/feature extraction process and the methodology for making the comparison are described. Performance of the methods is evaluated in terms of estimated percentage of correctly classified subjects.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0018-9294
pubmed:author
pubmed:issnType
Print
pubmed:volume
42
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
428-32
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
1995
pubmed:articleTitle
Brain maturation estimation using neural classifier.
pubmed:affiliation
Department of Applied Physics, University of La Laguna, Tenerife, Canary Islands, Spain.
pubmed:publicationType
Journal Article, Comparative Study