Linked Life Data

17512260

Source:http://linkedlifedata.com/resource/pubmed/id/17512260

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2008-1-16
pubmed:abstractText
In this study, we proposed a new medical diagnosis system based on principal component analysis (PCA), k-NN based weighting pre-processing, and Artificial Immune Recognition System (AIRS) for diagnosis of atherosclerosis from Carotid Artery Doppler Signals. The suggested system consists of four stages. First, in the feature extraction stage, we have obtained the features related with atherosclerosis disease using Fast Fourier Transformation (FFT) modeling and by calculating of maximum frequency envelope of sonograms. Second, in the dimensionality reduction stage, the 61 features of atherosclerosis disease have been reduced to 4 features using PCA. Third, in the pre-processing stage, we have weighted these 4 features using different values of k in a new weighting scheme based on k-NN based weighting pre-processing. Finally, in the classification stage, AIRS classifier has been used to classify subjects as healthy or having atherosclerosis. Hundred percent of classification accuracy has been obtained by the proposed system using 10-fold cross validation. This success shows that the proposed system is a robust and effective system in diagnosis of atherosclerosis disease.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1532-0480
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
41
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
15-23
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Medical diagnosis of atherosclerosis from Carotid Artery Doppler Signals using principal component analysis (PCA), k-NN based weighting pre-processing and Artificial Immune Recognition System (AIRS).
pubmed:affiliation
Erciyes University, Department of Electronics Engineering, 38039 Kayseri, Turkey. fdirgenali@tse.org.tr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't