Application of neural networks to the follow-up of AIDS patients.
The present work aims to obtain groups of patients with similar profiles of p24 antigen concentration and of CD4+ cell counts. These two markers were chosen because their evaluation represents a significant step in the clinical follow up of HIV-1 infected subjects. The classifications were obtained by a Kohonen neural net trained in three ways: with p24 antigen profiles only, with CD4+ cell count profiles only and with both sets of profiles. The results show that the clustering fashion of the two parameters closely resembles the clustering fashion of CD4+ only rather than the one of p24Ag, both with reference to cluster formation and with reference to distance among clusters.
Giacomini
M
M
DIST, Department of Communications Computer and System Sciences, University of Genova, Italy.
Ruggiero
C
C
Maillard
M
M
Lillo
F B
FB
Varnier
O E
OE
D000163:Acquired Immunodeficiency Syndrome / Q000175:diagnosis*; D000465:Algorithms; D015415:Biomarkers; D018791:CD4 Lymphocyte Count; D016655:HIV Core Protein p24 / Q000097:blood; D015497:HIV-1; D006801:Humans; D016571:Neural Networks, Computer; D011379:Prognosis