Hidden Markov Model of Evaluation of Break-Even Point of HIV patients: A Simulation Study

,Mahalakshmi Rajendran,Balasubramaniam Ramakrishnan,Senthamarai Kannan Kaliyaperumal

doi:10.55349/ijmsnr.2021121922

Abstract

Background: The HIV virus carries projection of significant global population with specific estimations of the mathematical results of evolutionary methods which was presented in Tree Hidden Markov model (HMM). Materials and Methods: Hidden Markov models used to model the progression of the disease among HIV infected people. The author predicts a Baum Welch Algorithm method through HMM that can assess an unknown state of transition. Results: The Tree HMM model predicts the break down point starts once patient is infected with the HIV virus as it affects the immune system. The immune system drops more quickly in the initial inter arrival time when compared with the later time interval. The HIV virus length in the nth state within regrouping is uncertain to occur in each state of the given model. A simulation study was done to assess the goodness of fit for the model. Conclusion: The HIV virus length in the nth state within regrouping is uncertain to occur in each state of the given model. The inter arrival censoring between each state is essential in each infected HIV patients. The outcome of this works states that health care expert can use this model for effective patient cares. Keywords: expectation, hidden markov model, human immunodeficiency virus, immune system, transition

Highlights

Twenty-Six million people in 2020 June, were assessing the human immunodeficiency virus (HIV) antiretroviral therapy when compared to 2019 end an estimation of 25.4 million, an estimated 2.4% of increase was observed
The three states are defined as; First state the initial state of HIV infection identified and under treatment; Second State identified as the person infected under HIV after some period of initial time period; Third state observes the later time period of the infected person
The Tree Hidden Markov Model (HMM) model predicts the break down point starts once patient is infected with the HIV virus as it affects the immune system

Summary

Introduction

Twenty-Six million people in 2020 June, were assessing the human immunodeficiency virus (HIV) antiretroviral therapy when compared to 2019 end an estimation of 25.4 million, an estimated 2.4% of increase was observed. The 69th World Wellbeing Gathering proposed a "Worldwide wellbeing area technique on HIV for 2016-2021”. [2] UNAIDS has set a 2030 cutoff time for the destruction of the HIV pandemic, which will match with World Guides Day in 2014. South India was the main region to be hit by the HIV pandemic since it had the most noteworthy populace thickness at that point. The HIV virus carries projection of significant global population with specific estimations of the mathematical results of evolutionary methods which was presented in Tree Hidden Markov model (HMM)

Methods

Results

Conclusion