Estimating and predicting the numbers of free HIV and T cells by nonlinear Kalman filter method

Author

Tan, Wai-Yuan ; Xiang, Zhihua

Author_Institution

Dept. of Math. Sci., Univ. of Memphis, TN, USA

Volume

1

fYear

1997

fDate

12-15 Oct 1997

Firstpage

386

Abstract

In this paper we have developed a state space model for the HIV pathogenesis at the cellular level involving free HIV and different types of T cells. In this state space model, the stochastic system model is the stochastic model of the HIV pathogenesis developed by Tan and Wu (1996) whereas the observation model is a statistic model based on the log of observed total numbers of CD4⁺ T-cell counts at different times. This is a continuous time-discrete time nonlinear Kalman filter model. For this model we have developed procedures for estimating and predicting the numbers of different types of T cells and free HIV through extended Kalman filter method. As an illustration, we have applied the method of this paper to a hemophilia patient from NCI/NIH with observed CD4⁺ T-cell counts at 16 occasions

Keywords

Kalman filters; continuous time filters; discrete time filters; estimation theory; health care; nonlinear filters; prediction theory; state-space methods; stochastic systems; HIV; T cells; continuous time filter; discrete time filter; hemophilia patient; nonlinear Kalman filter; number prediction; pathogenesis; state space model; statistic model; stochastic system; Biological system modeling; Cells (biology); Differential equations; Human immunodeficiency virus; Pathogens; State-space methods; Statistics; Stem cells; Stochastic processes; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.625780

Filename

625780