Analyzing progression of diseases is vital to monitor patient's traversal over time through a disease. Clinical study settings present modeling challenges, as patients' disease trajectories are only partially observed, and patients' disease statuses are only assessed at clinic vi...
Open access
Research Article10.9734/arrb/2019/v31i330049
Objective: This paper aims to compare various Bayesian joint models based on the accelerated failure time distributions in analyzing longitudinal observations on CD4 cell counts as growth measurements and time-to-death events of HIV/AIDS patients. Three accelerated failure time d...
Open access
Research Article10.9734/BJMMR/2017/32123
Background: Several factors may affect heart failure status of patients. It is important to investigate whether or not the effects are direct. The purpose of this study was learning Bayesian networks that encode the joint probability distribution for a set of random variables. Me...
The purpose of this study was to investigate the impact of risk factors on the death of patients with heart failure in a cohort of patients hospitalized with heart failure disease. In this paper we used chi-square tests with the aim of studying the relationship of each factor wit...