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Multivariate classification based on metal contents in human senile cataract lenses

Authors
Journal
Analytica Chimica Acta
0003-2670
Publisher
Elsevier
Publication Date
Volume
242
Identifiers
DOI: 10.1016/0003-2670(91)87041-5
Keywords
  • Pattern Recognition
  • Eye Cataracts
  • Trace Metals

Abstract

Abstract Multivariate classification methods were used to evaluate data on the concentrations of eight metals in human senile lenses measured by atomic absorption spectrometry. Principal components analysis and hierarchical clustering separated senile cataract lenses, nuclei from cataract lenses, and normal lenses into three classes on the basis of the eight elements. Stepwise discriminant analysis was applied to give discriminant functions with five selected variables. Results provided by the linear learning machine method were also satisfactory; the k-nearest neighbour method was less useful.

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