An application of linear programming discriminant analysis to classifying and predicting the symptomatic status of HIV/AIDS patients.
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.
Department of Decision Sciences and MIS, St. Louis University, Missouri 63108 USA. kwakn@slu.edu
N K
NK
Kwak
Seong Ho
SH
Kim
Chang W
CW
Lee
Tae Sung
TS
Choi
D003936:Diagnosis, Computer-Assisted; D016002:Discriminant Analysis; D005260:Female; D015658:HIV Infections / Q000145:classification / Q000503:physiopathology*; D006801:Humans; D008297:Male; D011382:Programming, Linear; D012720:Severity of Illness Index