Statements in which the resource exists.
SubjectPredicateObjectContext
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pubmed-article:15344451pubmed:dateCreated2004-9-3lld:pubmed
pubmed-article:15344451pubmed:abstractTextThis 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.lld:pubmed
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pubmed-article:15344451pubmed:authorpubmed-author:WangLei ELElld:pubmed
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pubmed-article:15344451pubmed:volume18lld:pubmed
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pubmed-article:15344451pubmed:pagination114-25lld:pubmed
pubmed-article:15344451pubmed:dateRevised2007-11-14lld:pubmed
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pubmed-article:15344451pubmed:year2003lld:pubmed
pubmed-article:15344451pubmed:articleTitleFeature selection for shape-based classification of biological objects.lld:pubmed
pubmed-article:15344451pubmed:affiliationMedical Image Display and Analysis Group, University of North Carolina, Chapel Hill, NC, USA pauly@cs.unc.edulld:pubmed
pubmed-article:15344451pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:15344451pubmed:publicationTypeClinical Triallld:pubmed
pubmed-article:15344451pubmed:publicationTypeComparative Studylld:pubmed
pubmed-article:15344451pubmed:publicationTypeResearch Support, U.S. Gov't, P.H.S.lld:pubmed
pubmed-article:15344451pubmed:publicationTypeControlled Clinical Triallld:pubmed
pubmed-article:15344451pubmed:publicationTypeValidation Studieslld:pubmed