Linked Life Data

17188902

Source:http://linkedlifedata.com/resource/pubmed/id/17188902

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2007-2-6
pubmed:abstractText
We proposed pattern classification based on principal components of cortical thickness between schizophrenic patients and healthy controls, which was trained using a leave-one-out cross-validation. The cortical thickness was measured by calculating the Euclidean distance between linked vertices on the inner and outer cortical surfaces. Principal component analysis was applied to each lobe for practical computational issues and stability of principal components. And, discriminative patterns derived at every vertex in the original feature space with respect to support vector machine were analyzed with definitive findings of brain abnormalities in schizophrenia for establishing practical confidence. It was simulated with 50 randomly selected validation set for the generalization and the average accuracy of classification was reported. This study showed that some principal components might be more useful than others for classification, but not necessarily matching the ordering of the variance amounts they explained. In particular, 40-70 principal components rearranged by a simple two-sample t-test which ranked the effectiveness of features were used for the best mean accuracy of simulated classification (frontal: (left(%)|right(%))=91.07|88.80, parietal: 91.40|91.53, temporal: 93.60|91.47, occipital: 88.80|91.60). And, discriminative power appeared more spatially diffused bilaterally in the several regions, especially precentral, postcentral, superior frontal and temporal, cingulate and parahippocampal gyri. Since our results of discriminative patterns derived from classifier were consistent with a previous morphological analysis of schizophrenia, it can be said that the cortical thickness is a reliable feature for pattern classification and the potential benefits of such diagnostic tools are enhanced by our finding.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1053-8119
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
34
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1405-15
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia.
pubmed:affiliation
Department of Biomedical Engineering, Hanyang University, Sungdong PO Box 55, Seoul 133-605, Korea.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't