Medicine and Health Sciences Commons^™

Gardasil Vaccine Trends Within Nevada, California, And The U.S.: A Comparative Study, Karen S. Gutierrez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Despite decreasing incidence in cervical cancer in the U.S., there continues to be an increase in public health concern for cervical cancer worldwide. Recent studies report that individuals are disproportionately affected based on region, sex, and race. Additionally, the human papillomavirus (HPV) attributable cancers may be reduced between 70% and 90% through the universal use of HPV-vaccines. In order to expand current knowledge and implement intervention programs in Nevada, it is critical to examine the associations among the Gardasil vaccine, cervical cancer screening, and adverse events following immunization as well as to understand the different socio-demographic subgroups affected. To our …

Comparison Of Longitudinal Changes In Resting State Functional Magnetic Resonance Imaging Between Alzheimer’S And Healthy Controls, Berk Can Yilmaz

Theses

Resting State Functional Magnetic Resonance Imaging (rs-fMRI) is a technique that is widely used for analyzing brain function using different approaches and methods. This study involves rs-fMRI analysis of Blood Oxygenation Level Dependent (BOLD) signals acquired from Alzheimer’s disease (AD) Patients and Healthy Controls (HC). Each subject in the study had both functional and anatomical images with at least one rs-fMRI scan with their Anatomical (T1) scans. Previous rs-fMRI studies have demonstrated that AD shows differences in Amplitude of Low Frequency (<0.1 Hz) Fluctuations (ALFF), and Regional Homogeneity (ReHo) measures according to HCs.

The aim of the study is to investigate individual and group level differences using ReHo and mALFF related …

Machine-Learning-Based Prediction Of Sepsis Events From Vertical Clinical Trial Data: A Naïve Approach, Tyler Michael Gaddis

Theses and Dissertations

Sepsis is a potentially life-threatening condition characterized by a dysregulated, disproportionate immune response to infection by which the afflicted body attacks its own tissues, sometimes to the point of organ failure, and in the worst cases, death. According to the Centers for Disease Control and Prevention (CDC) Sepsis is reported to kill upwards of 270,000 Americans annually, though this figure may be greater given certain ambiguities in the current accepted diagnostic framework of the disease.

This study attempted to first establish an understanding of past definitions of sepsis, and to then recommend use of machine learning as integral in an …

Statistical Methods For Resolving Intratumor Heterogeneity With Single-Cell Dna Sequencing, Alexander Davis

Dissertations & Theses (Open Access)

Tumor cells have heterogeneous genotypes, which drives progression and treatment resistance. Such genetic intratumor heterogeneity plays a role in the process of clonal evolution that underlies tumor progression and treatment resistance. Single-cell DNA sequencing is a promising experimental method for studying intratumor heterogeneity, but brings unique statistical challenges in interpreting the resulting data. Researchers lack methods to determine whether sufficiently many cells have been sampled from a tumor. In addition, there are no proven computational methods for determining the ploidy of a cell, a necessary step in the determination of copy number. In this work, software for calculating probabilities from …

"A Comparison Of Variable Selection Methods Using Bootstrap Samples From Environmental Metal Mixture Data", Paul-Yvann Djamen

Mathematics & Statistics ETDs

In this thesis, I studied a newly developed variable selection method SODA, and three customarily used variable selection methods: LASSO, Elastic net, and Random forest for environmental mixture data. The motivating datasets have neuro-developmental status as responses and metal measurements and demographic variables as covariates. The challenges for variable selections include (1) many measured metal concentrations are highly correlated, (2) there are many possible ways of modeling interactions among the metals, (3) the relationships between the outcomes and explanatory variables are possibly nonlinear, (4) the signal to noise ratio in the real data may be low. To compare these methods …

An Improved Method For Spectroscopic Quality Classification, Elizabeth G. Mayer

Mathematics & Statistics ETDs

Spectral quality classification is a vital step in data cleaning before the

analysis of magnetic resonance spectroscopy (MRS) data can be done. This

analysis compares five methods of quality classification; three of these are

legacy methods, Maudsley et al. (2006), Zhang et al. (2018), and

Bustillo et al. (2020), and two newly created methods that used a random forests

classifier (RFC) to inform their classifications. We found that the random forest

classifier was the most accurate at predicting spectra quality (balanced

accuracy for RF of 88% vs legacy of 70%, 72%, or 72%). A

Random-Forests-Informed Filtering method (RFIFM) for quality …

Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang

USF Tampa Graduate Theses and Dissertations

The world’s population is rapidly aging and the increasing demand for home and health care services from this aging population brings unprecedented challenges to the economy and society. Ambient-assisted smart homes, residences equipped with ambient sensors to monitor the resident’s daily activities in a continuous and unobtrusive way, present great potential to manage the growing care service needs of this older population segment, and enable them to age-in-place.

Despite growing research, using ambient sensor data from private homes to monitor daily activities, health and wellness still faces significant challenges. To study ambient sensor data from private homes where annotated data …

Infant Mortality In The United States: Socioeconomic Factors Predicting Infant Survival In Late Neo-Natal And Post Neo-Natal Infants From Birth Certificate Data, Mark Brunk-Grady

Theses and Dissertations

According to the Centers for Disease Control and Prevention, the infant mortality rate in the United States in 2018 was 5.6 deaths per 1000 live births. Infant mortality is defined as a child being born alive but dying before their first birthday. This study aimed to determine if adding socioeconomic factors to traditional predictive survival models improved the predictive power in terms of survival for late and post neonatal infants. Secondly, this study looked to develop a risk score to and predict which mothers would be classified as “High” or “Low” risk for infant death.

Data were analyzed from a …

Physical Therapy Nontreatment Events With Primary Physical Therapist, Stephen Johnson

UNLV Theses, Dissertations, Professional Papers, and Capstones

Background: Physical therapy improves prognosis reduces stay and is generally helpful in aiding recovery from a wide range of ailments. Nontreatment rates occur for multiple reasons and are also related to the personalities of physical therapists.

Methods: We used data from a research project involving physical therapy at an acute care facility in our community. Our study focused on the retrospectively determined primary physical therapist for each patient. We used the chi-squared tests to compare nontreatment rates between days of the week and disease type and the reasons for nontreatment events. Repeated-measure models were used to evaluate the effect of …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is …

Equivalency Testing For Two Formulations Of A Clinical Laboratory Control Material, Jessica M. Hart

Capstone Experience

Clinical laboratory control materials are an integral part of legally-mandated and highly regulated quality control protocols in all clinical laboratories. These controls ensure accurate performance of the laboratory testing and instrumentation used to produce medical test results for millions of patients. It is of clinical and public health interest to ensure the diagnostic test results which affect so many people are regulated by the most accurate and precise controls.

Formulation changes in control materials have the potential to impact laboratory quality control. In this study, data from two formulations of a hematology control were compared to assess equivalency of the …

Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya

Electronic Theses and Dissertations

Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …

Exploration Of Factors Associated With Perceptions Of Community Safety Among Youth In Hillsborough County, Florida: A Convergent Parallel Mixed-Methods Approach, Yingwei Yang

USF Tampa Graduate Theses and Dissertations

Introduction: Youth perceived safety is not only linked to crime and violence in a neighborhood but is also associated with health risk behaviors and certain neighborhood characteristics. The purpose of this mixed-methods study was to measure the co-occurring effects of individual and community risk factors by conducting a secondary data analysis using structural equation modeling (SEM) and to explore reasons for youth feeling safe/unsafe in their community using photovoice methodology.

Methods: Syndemic theory/model served as the theoretical framework to guide this mixed-methods study with a convergent parallel design. The quantitative strand (first manuscript) utilized an existing dataset collected from middle …

Nutrition And Health Status Of Hemodialysis Patients In Dhaka, Bangladesh, Tanjina Rahman

Wayne State University Dissertations

Methods to identify patients at risk for End stage renal disease (ESRD) are a high priority in Bangladesh, where kidney transplants/dialysis options are limited and costly. Every year, 35,000 to 40,000 people reach ESRD in Bangladesh, but currently available facilities can hardly accommodate only 9000 to 10,000 new patients with twice weekly dialysis and the remaining 66% have no access to any kind of renal replacement therapy (RRT) in the form of dialysis or transplantation. Nutrition is an important factor in maintaining good health of hemodialysis patients. However, data on nutritional status of Bangladeshi dialysis patients is limited and is …

The Experiences Of Ncaa Student-Athletes With An Eating Disorder Or Disordered Eating, Rachel E. Taylor

Electronic Theses and Dissertations

The purpose of this study was to explore the experiences of student-athletes who had an eating disorder or disordered eating (ED/DE) while competing for the National Collegiate Athletic Association (NCAA). Integrating criticism and connoisseurship and critical evocative portraiture, four post-collegiate women who participated in cross country and track, who were either clinically diagnosed with an ED/DE or who self-diagnosed, participated in two interviews to describe their experiences with and the impact of ED/DE on their athletic pursuits, academic pursuits, as well as their relationships with coaches, teammates, and family. The analysis of these interviews showed the complexity of this topic. …

How 6-12th Grade Staff Support Students With Depression: A Pilot Study To Develop Measures Of Implicit Associations, Explicit Attitudes And Helping Behavior, Paul M. Thompson

Electronic Theses and Dissertations

Students with emotional disabilities are disproportionately suspended and expelled in K-12 schools. Attribution theory suggests individuals are less likely to provide assistance to others if they believe the individuals are responsible for their own difficulties. To test attribution theory, this study created new measures of explicit attitudes and implicit associations of licensed 6-12th grade staff regarding students with depression as well as a helping behavior measure of staff toward students with depression. The survey was distributed within a single school district in the western United States. A majority of the sample (N = 52) held a mental health license (60%), …

Predictors Of Colorectal Cancer Screening Among Maryland Adults, Aged 50–75 Years, Pamela Manwi Asangong

Walden Dissertations and Doctoral Studies

Screening plays an essential role in reducing colorectal cancer (CRC) incidence and mortality rates, yet CRC screening use remains low in Maryland and lower in some age and racial/ethnic groups with limited resources to participate in CRC screening programs. The purpose of this quantitative, cross-sectional study is to investigate whether age group, sex, race/ethnicity, education level, income level, health insurance coverage, and access to health care professional can predict an individual, 50–75 years of age, in Maryland to take action to fully meet the United States Preventive Services Task Force CRC screening test recommendation within the recommended time interval. The …

Lifestyle Factors And Social Determinants As Predictors Of Weight/Body Mass Index, Uthman Alhaji Baba

Walden Dissertations and Doctoral Studies

Obesity is a major public health concern that includes the risk of developing cardiovascular disease and premature death in adults. Previous studies have established the relationship between gender, educational level, household income and respondents’ weight but additional research is needed to factor the nature of education in relation to gender differences, diet, and other important behavioral mediators such as social determinants. The purpose of this quantitative cross-sectional study is to determine the extent to which frequency of physical activity, household income, social determinants of health (money for balanced meals, finances at the end of month, and poor mental health), respondent …

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya

Graduate Theses, Dissertations, and Problem Reports

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …

Novel Random Forest Methods And Algorithms For Autism Spectrum Disorders Research, Afrooz Jahedi

CGU Theses & Dissertations

Random Forest (RF) is a flexible, easy to use machine learning algorithm that was proposed by Leo Breiman in 2001 for building a predictor ensemble with a set of decision trees that grow in randomly selected subspaces of data. Its superior prediction accuracy has made it the most used algorithms in the machine learning field. In this dissertation, we use the random forest as the main building block for creating a proximity matrix for multivariate matching and diagnostic classification problems that are used for autism research (as an exemplary application). In observational studies, matching is used to optimize the balance …

A Comparative Spatial And Climate Analysis Of Human Granulocytic Anaplasmosis And Human Babesiosis In New York State (2013-2018), Collin J. O'Connor

Legacy Theses & Dissertations (2009 - 2024)

Human granulocytic anaplasmosis (HGA) and human babesiosis are tick-borne diseases spread by Ixodes scapularis (the blacklegged or deer tick) and are the result of infection with Anaplasma phagocytophilum and Babesia microti, respectively. In New York State (NYS), incidence rates of these diseases increased concordantly until around 2013, when rates of HGA began to increase more rapidly than human babesiosis, and the spatial extent of the diseases diverged. Surveillance data of tick-borne pathogens (2007 to 2018) and reported human cases of HGA (n=4,297) and human babesiosis (n=2,986) (2013 to 2018) from the New York State Department of Health (NYSDOH) showed a …

A Multinational Study Of The Etiology And Clinical Teleology Of Moral Evaluations Of Patient Behaviors, Anna Yu Lee

CGU Theses & Dissertations

This dissertation is a collection of four studies which collectively explore a hypothesized construct of ‘moral evaluation of patient behaviors’ (MEPB) as a driver of health professionals’ readiness to interact humanistically with their patients. In these studies, ‘humanistic interactions’ refer to the non-technical, intangible skills and factors of clinical competence; the factors specifically explored in these studies were compassion toward patients, self-efficacy for treating patients, and optimism toward patient treatment. For the purpose of specificity, all factors were examined as they pertained to patients with substance use disorders. Survey data from a convenience sample of 524 health professionals (i.e. physicians, …

The Application Of Machine Learning Models In The Concussion Diagnosis Process, Sujit Subhash

Masters Theses

“Concussions represent a growing health concern and are challenging to diagnose and manage. Roughly four million concussions are diagnosed every year in the United States. Although research into the application of advanced metrics such as neuroimages and blood biomarkers has shown promise, they are yet to be implemented at a clinical level due to cost and reliability concerns. Therefore, concussion diagnosis is still reliant on clinical evaluations of symptoms, balance, and neurocognitive status and function. The lack of a universal threshold on these assessments makes the diagnosis process entirely reliant on a physician’s interpretation of these assessment scores. This study …