scholarly journals Principal components analysis as a tool to identify lesional skin patterns in cutaneous lupus erythematosus

2020 ◽  
Vol 83 (3) ◽  
pp. 922-924
Author(s):  
Smriti Prasad ◽  
Justin Raman ◽  
Motolani E. Ogunsanya ◽  
Benjamin F. Chong
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Lupus Erythematosus ◽  
Cutaneous Lupus Erythematosus ◽  
Lesional Skin ◽  
Components Analysis ◽  
Cutaneous Lupus

Increased expression of guanylate binding protein-1 in lesional skin of patients with cutaneous lupus erythematosus

2010 ◽  
Vol 20 (2) ◽  
pp. 102-106 ◽  
Author(s):  
Elisabeth Naschberger ◽  
Jörg Wenzel ◽  
Cosima C. Kretz ◽  
Martin Herrmann ◽  
Michael Stürzl ◽  
...  
Keyword(s):  
Lupus Erythematosus ◽  
Binding Protein ◽  
Cutaneous Lupus Erythematosus ◽  
Lesional Skin ◽  
Guanylate Binding Protein ◽  
Cutaneous Lupus

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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