… with Model C, we incorporated proportional hazard models relating … Our analysis of TB
care-seeking, diagnosis and treatment … , or expectations of treatment may all affect and influence …

… analysis of the Bayesian network showed greatest influence on … in prey, and less influence
from toxicity reference values. … diagnostic, mixed, and predictive inference make Bayesian …

… interviews, series of laboratory tests and ECG recordings. The … and unweighted Cox
proportional hazard models with SPSS … that undiagnosed cases of CHD could have influenced the …

… The date of the first-time pregnancy diagnosis during the study period was assigned as
their … would influence the diagnosis obviously. And the statistic data and the analysis results …

… initial diagnosis of leukoplakia to the diagnosis of carcinoma. … cancer, a Bayesian mixture
cure model based on the Weibull … To perform the survival analysis based on the cure model, we …

… that of healthcare diagnosis, making the Bayesian network an … variables in the hazard model.
Following Tibshirani (1996), … 6, we select three pairs of influential variables and generate …

… Transition analysis, paired with Bayesian analysis, uses a … model assumes the effects of the
covariates upon survival … the Cox regression model was checked using tests of proportionality…

… the survival data from such trials using standard survival models … Recent progress in the
diagnosis and treatment of cancer has … Bayesian cure rate models induced by frailty in survival …

… Expert knowledge is translated into Bayesian networks for Fault Diagnosis. … , demonstrating
how the evidence from the detection process influences the results of the diagnosis process. …

… (tectonic and geological) and models (seismogenic sources, ground shaking). A fully
probabilistic framework was adopted in the hazard model implementation and all datasets and …