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Multistate Markov Chains And Their Application To The Biologically Resilient Adults In Neurological Studies Cohort, Erin L. Abner

Theses and Dissertations--Epidemiology and Biostatistics

Dementia is increasingly recognized as a major and growing threat to public health worldwide, and there is a critical need for prevention and treatment strategies. However, it is necessary that appropriate methodologies are used in the identification of risk factors. The purpose of this dissertation research was to develop further the body of literature featuring Markov chains as an analytic tool for data derived from longitudinal studies of aging and dementia.

Data drawn from 649 participants in the University of Kentucky’s Alzheimer’s Disease Center’s (UK ADC) Biologically Resilient Adults in Neurological Studies (BRAiNS) cohort, which was established in 1989 and …

The Psychological Impacts Of False Positive Ovarian Cancer Screening: Assessment Via Mixed And Trajectory Modeling, Amanda T. Wiggins

Theses and Dissertations--Epidemiology and Biostatistics

Ovarian cancer (OC) is the fifth most common cancer among women and has the highest mortality of any cancer of the female reproductive system. The majority (61%) of OC cases are diagnosed at a distant stage. Because diagnoses occur most commonly at a late-stage and prognosis for advanced disease is poor, research focusing on the development of effective OC screening methods to facilitate early detection in high-risk, asymptomatic women is fundamental in reducing OC-specific mortality. Presently, there is no screening modality proven efficacious in reducing OC-mortality. However, transvaginal ultrasonography (TVS) has shown value in early detection of OC. TVS presents …

Data Mining And Pattern Discovery Using Exploratory And Visualization Methods For Large Multidimensional Datasets, Hsin-Fang Li

Theses and Dissertations--Epidemiology and Biostatistics

Oral health problems have been a major public health concern profoundly affecting people’s general health and quality of life. Given that oral health data is composed of several measurable dimensions including clinical measurements, socio-behavioral factors, genetic predispositions, self-reported assessments, and quality of life measures, strategies for analyzing multidimensional data are neither computationally straightforward nor efficient. Researchers face major challenges to identify tools that circumvent the processes of manually probing the data.

The purpose of this dissertation is to provide applications of the proposed methodology on oral health-related data that go beyond identifying risk factors from a single dimension, and to …