scholarly journals Analyzing chemical data in more than two dimensions: A tutorial on factor and cluster analysis

1990 ◽  
Vol 67 (6) ◽  
pp. 461 ◽  
Author(s):  
Thomas P. E. Auf der Heyde
Keyword(s):  
Cluster Analysis ◽  
Two Dimensions ◽  
Chemical Data ◽  
Factor And Cluster Analysis ◽  
And Cluster Analysis

scholarly journals Pathways and Patterns of Cell Loss in Verified Alzheimer’s Disease: A Factor and Cluster Analysis of Clinico-Pathological Subgroups

1994 ◽  
Vol 7 (3-4) ◽  
pp. 175-180 ◽  
Author(s):  
H. Förstl ◽  
R. Levy ◽  
A. Burns ◽  
P. Luthert ◽  
N. Cairns
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cluster Analysis ◽  
Cell Loss ◽  
Cell Numbers ◽  
Cell Counts ◽  
Patient Groups ◽  
Components Analysis ◽  
Factor And Cluster Analysis ◽  
And Cluster Analysis

Thirty-seven patients with neuropathologically verified Alzheimer's disease (AD) have been studied prospectively. A principal components analysis of neuron numbers in cortical and subcortical areas revealed two variables: Variable I with high loadings for the hippocampo-parahippocampo-parietal neuron counts and Variable II with high loadings for coeruleo-frontal cell numbers. Both may reflect functional neuroanatomical connections which may act as pathways of neurodegeneration in AD. A cluster analysis based on these neuron numbers yielded three groups of patients: Cluster A with low hippocampo-parahippocampo-parietal cell counts, Cluster B with well-preserved neuron numbers, and Cluster C with low coeruleo-frontal neuron numbers. Differences in clinical features between these patient groups indicated the potential clinical relevance of these clusters.

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