Application of Radial Basis Function Network Tool for Correlation of CD4+ Count with Plasma Viral Load in HIV-Seropositive Individuals.

Abstract

Human Immunodeficiency Virus (HIV) infects and cripples the immune system of the body. The two important marker CD4+T cells and Plasma viral load are crucial not only in understanding the disease progression but also in starting the antiretroviral therapy. A lot of research is going on in understanding the dynamic nature of HIV. To find the correlation between CD4+ count and Plasma Viral Load (PVL) measured by two different technologies; with the help of correlation technique in conjunction with the three dimensional HIV model with a purpose of establishing a mathematical model between the CD4+ cells and PVL using a sinusoidal function as well as Radial Basis Function (RBF) neural network. Plasma Viral Load were determined by two different methods viz Exavir Cavidi(TM) and Abbott Real time HIV-1 assay and then they were correlated with the CD4+ count with the help of computational intelligence in predicting viral load. It was found that there exists a positive correlation between the CD4+ cells and viral loads. A correlation value of 0.4082 and 0.3652 was observed between CD4+ cells and viral measured using Exavir Cavidi(TM) and Abbott Real time HIV-1 assay respectively. The existence of positive correlation had helped us to understand the nature and dynamic of the existence of HIV and how the CD4 + and PVL act.