Linked Life Data

15344451

Source:http://linkedlifedata.com/resource/pubmed/id/15344451

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2004-9-3
pubmed:abstractText
This paper introduces a method for selecting subsets of relevant statistical features in biological shape-based classification problems. The method builds upon existing feature selection methodology by introducing a heuristic that favors the geometric locality of the selected features. This heuristic effectively reduces the combinatorial search space of the feature selection problem. The new method is tested on synthetic data and on clinical data from a study of hippocampal shape in schizophrenia. Results on clinical data indicate that features describing the head of the right hippocampus are most relevant for discrimination.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1011-2499
pubmed:author
pubmed:issnType
Print
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
114-25
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Feature selection for shape-based classification of biological objects.
pubmed:affiliation
Medical Image Display and Analysis Group, University of North Carolina, Chapel Hill, NC, USA pauly@cs.unc.edu
pubmed:publicationType
Journal Article, Clinical Trial, Comparative Study, Research Support, U.S. Gov't, P.H.S., Controlled Clinical Trial, Validation Studies