Principal component analysis in the evaluation of osteoarthritis

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ID: 274523
2017
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Ranked #18 of 18 articles by views in american journal of physical anthropology

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Abstract
PCA is a simple, non-parametric method of extracting relevant information from complex OA datasets and summarizes variation based on correlated multi-attributes to reveal a simplified structure of OA expression. Multivariate techniques like PCA should be used to describe discrete OA samples, and are …
Reference Key
se2017americanprincipal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Calce SE;Kurki HK;Weston DA;Gould L;;
Journal american journal of physical anthropology
Year 2017
DOI
DOI not found
URL
https://www.ncbi.nlm.nih.gov/pubmed/27896800
Keywords
National Center for Biotechnology Information NCBI NLM MEDLINE humans pubmed abstract nih national institutes of health national library of medicine adult female male adolescent aged middle aged young adult 80 and over multivariate analysis anthropology pmid:27896800 doi:10.1002/ajpa.23130 stephanie e calce helen k kurki lisa gould physical lumbar vertebrae / pathology osteoarthritis / diagnosis* osteoarthritis / pathology* principal component analysis / methods* sacrum / pathology tibia / pathology

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