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Full-Text Articles in Medicine and Health Sciences
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Electronic Theses and Dissertations
Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …
Post-Diagnosis Quality Of Life And Mortality In Non-Hispanic White And Hispanic Women Diagnosed With Invasive Breast Cancer., Delvon T. Mattingly
Post-Diagnosis Quality Of Life And Mortality In Non-Hispanic White And Hispanic Women Diagnosed With Invasive Breast Cancer., Delvon T. Mattingly
Electronic Theses and Dissertations
The prevalence of breast cancer is increasing, and the health-related quality of life (HRQOL) of breast cancer survivors may help to further understand survivorship. This study evaluated HRQOL as a potential prognostic factor for mortality among Non-Hispanic White (NHW) and Hispanic women diagnosed with invasive breast cancer. Data were used from the Health, Eating, Activity, and Lifestyle (HEAL) Study. Data for 351 participants were analyzed for associations between HRQOL scores (subscale, component) and mortality. Cox proportional hazards regression was conducted to assess the relationship between HRQOL and mortality outcomes (all-cause, breast cancer-specific, non-cancer). Median follow-up time from HRQOL assessment (approximately …