Application of neural networks to the follow-up of AIDS patients

Abstract

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.