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Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray
Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray
Theses and Dissertations
Functional neuroimaging is a relatively young discipline within the neurosciences that has led to significant advances in our understanding of the human brain and progress in neuroscientific research related to public health. Accurately identifying activated regions in the brain showing a strong association with an outcome of interest is crucial in terms of disease prediction and prevention. Functional magnetic resonance imaging (fMRI) is the most widely used method for this type of study as it has the ability to measure and identify the location of changes in tissue perfusion, blood oxygenation, and blood volume. In practice, the three-dimensional brain locations …
Non- And Semi-Parametric Bayesian Inference With Recurrent Events And Coherent Systems Data, A. K. M. Fazlur Rahman
Non- And Semi-Parametric Bayesian Inference With Recurrent Events And Coherent Systems Data, A. K. M. Fazlur Rahman
Theses and Dissertations
This dissertation deals with non- and semi-parametric Bayesian inference of gap-time distribution with recurrent event data and simultaneous inference of component and system reliabilities of coherent systems data. Recurrent event data arise from a wide variety of studies/fields such as clinical trials, epidemiology, public health, biomedicine (e.g. repeated heart attack, repeated tumor occurrences of a cancer patient). In Chapter 2 we develop nonparametric Bayes and empirical Bayes estimators of the survivor function \bar{F} = 1 - F, of the gap-time distribution by assigning a Dirichlet process prior on F. We develop a closed form estimator of \bar{F} as well as …