Literature DB >> 12182207

An application of linear programming discriminant analysis to classifying and predicting the symptomatic status of HIV/AIDS patients.

N K Kwak1, Seong Ho Kim, Chang W Lee, Tae Sung Choi.   

Abstract

This study presents an application of linear programming discriminant analysis (LPDA) to classify and to predict the symptomatic status of HIV/AIDS patients. We applied LPDA as well as several traditional discriminant analysis methods to the AIDS Cost and Services Utilization Survey data set in order to demonstrate the use of LPDA to classify the symptomatic status of HIV/AIDS patients. The potential benefit of LPDA in terms of the classification accuracy was also analyzed.

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Year:  2002        PMID: 12182207     DOI: 10.1023/a:1016496916732

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  3 in total

1.  Mathematical Programming Approaches for the Classification Problem in Two-Group Discriminant Analysis.

Authors:  E A Joachimsthaler; A Stam
Journal:  Multivariate Behav Res       Date:  1990-10-01       Impact factor: 5.923

2.  Some examples of discrimination.

Authors:  C A B SMITH
Journal:  Ann Eugen       Date:  1947-06

3.  A neural network application to classification of health status of HIV/AIDS patients.

Authors:  N K Kwak; C Lee
Journal:  J Med Syst       Date:  1997-04       Impact factor: 4.460

  3 in total

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