Biostatistics Commons^™

Deep Learning-Based Technique For The Perception Of The Cervical Cancer, Aya Haraz, Hossam El-Din Moustafa, Abeer Twakol Khaleel, Ahmed H. Eltanboly

Mansoura Engineering Journal

In third-world countries, cervical cancer is the most prevalent and leading cause of death. It is affected by a variety of factors, including smoking, poor nutritional status, immunological inadequacy, and prolonged use of contraception. The Pap smear test, which is intended to prevent cervical cancer, finds preneoplastic changes in cervical epithelial cells. This study framework classified cervical cancer cells from Pap smears into five specified cell types using machine learning-based classification algorithms. The SIPaKMeD database is used in this investigation. This public dataset, which was manually cropped from 966 cluster cell images taken from Pap smear slides, has 4045 isolated …

Modeling The Bidirectional Relationship Between Shared-Patient Physician Networks And Patient Longitudinal Treatment Patterns: Application To Physician Risky-Prescribing, Xin Ran

Dartmouth College Ph.D Dissertations

Risky-prescribing is a pressing public health concern in the United States. Opioids, benzodiazepines, and non-benzodiazepine sedative-hypnotics (sedative-hypnotics) are three commonly-prescribed but potentially risky drug groups, prescribed alone or in combination. Physician shared-patient networks provide a unique perspective in studying physician network characteristics and structures, as well as their association with the delivery of health care. Understanding how physician shared-patient networks are related to their prescribing may inform network-based interventions targeting risky-prescribing, which is yet to be fully studied.

We investigated patient receipt of risky prescriptions and physician risky-prescribing intensity through the scope of shared-patient networks. We used retrospective Medicare insurance …

Variability In Causal Effects On A Binary Outcome And Noncompliance In A Multisite Randomized Trial, Xinxin Sun

Theses and Dissertations

Noncompliance to treatment assignment is widespread in randomized trials and presents challenges in causal inference. In the presence of noncompliance, the most commonly estimated effect of treatment assignment, also known as intent-to-treat (ITT) effect, is biased. Of interest in this setting is the complier average causal effect (CACE), the ITT effect among compliers. Further complication arises when the outcome variable is partially observed.

My research focuses on estimating the distribution of a site-specific CACE in a multisite randomized controlled trial (MRCT) by maximum likelihood (ML). Assuming compliance missing at random (MAR). We express the likelihood as an integral with respect …

Integrative Post-Gwas Analyses Of Psychiatric Disorders: Identifying Putative Risk Genes And Gene Sets Using Transcriptome, Proteome And Methylome Information, Huseyin Gedik

Theses and Dissertations

Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often they do not implicate specific protein coding genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS), which integrate information from GWAS and x-level (mRNA, protein or DNA methylation levels) coming from largest xQTL studies, can link GWAS signals to effects on specific genes. For gene level analyses, researchers use mendelian randomization (MR) methods to fine-map the association between x-levels and trait. However, none of the previous studies ever jointly analyzed XWAS of multiple …

Model-Based Imputation Of Below Detection Limit Missing Data And Group Selection In Bayesian Group Index Regression, Matthew Carli

Theses and Dissertations

Investigations into the association between chemical exposure and health outcomes are increasingly focused on the role of chemical mixtures, as opposed to individual chemicals. The analysis of chemical mixture data required the development of novel statistical methods, one of these being Bayesian group index regression. A statistical challenge common to all chemical mixture analyses is the ubiquitous presence of below detection limit (BDL) data. We propose an extension of Bayesian group index regression that treats both regression effects and missing BDL observations as parameters in a model estimated through a Markov Chain Monte Carlo algorithm that we refer to as …

Reassessing Replication: Addressing The Replication Crisis From A Statistical Perspective, Alicia Richards Phd

Theses and Dissertations

In 2015, Open Science Framework directly replicated 100 psychology studies and found astonishingly low replication rates. Since, researchers have suggested factors that may have influenced the low rates, including the metrics used to assess replications. The definitions used to decide whether a replication study was successful all suffer from flaws. Therefore, we propose a new metric for assessing replication that can estimate the likelihood a study successfully replicated rather than forcing a binary choice and accounts for study design limitations.

Using equivalence study techniques, we first propose a new metric to assess replication, defining a successful replication as one where …

The Birds And The Trees: Quantifying The Drivers Of Whitebark Pine Decline And Clark's Nutcracker Habitat Use In Glacier National Park, Vladimir Kovalenko

Graduate Student Theses, Dissertations, & Professional Papers

Whitebark pine (Pinus albicaulis), recently listed as threatened under the Endangered Species Act, is in steep decline in Glacier National Park, Montana, USA due to the non-native pathogen Cronartium ribicola, causal agent of the fatal disease white pine blister rust. A sample of the park’s population suggests that approximately 70 percent of whitebark pines have died, while 65 percent of the remaining trees are infected. Using landscape and climate variables, we show how geographic location, elevation, aspect, solar radiation, relative humidity, and snowpack interact with tree diameter to affect mortality, disease incidence, cone production, and regeneration. We also examine how …

Turnover, Covid-19, And Reasons For Leaving And Staying Within Governmental Public Health, Jonathan P. Leider, Gulzar H. Shah, Valerie A. Yeager, Jingjing Yin, Kusuma Madamala

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Background and Objectives:

Public health workforce recruitment and retention continue to challenge public health agencies. This study aims to describe the trends in intention to leave and retire and analyze factors associated with intentions to leave and intentions to stay.

Design:

Using national-level data from the 2017 and 2021 Public Health Workforce Interests and Needs Surveys, bivariate analyses of intent to leave were conducted using a Rao-Scott adjusted chi-square and multivariate analysis using logistic regression models.

Results:

In 2021, 20% of employees planned to retire and 30% were considering leaving. In contrast, 23% of employees planned to retire and 28% …

On Kernel-Based Estimator Of Odds Ratio Using Different Stratified Sampling Schemes, Abbas Eftekharian, Hani Samawi, Haresh Rochani

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.

Association Of Chlorhexidine Use And Scaling And Root Planing With Birth Outcomes In Pregnant Individuals With Periodontitis: A Systematic Review And Meta-Analysis, Maxwell Akonde, Rajat Das Gupta, Maxwell Akonde, Mark Reynolds, Stephanie Smith-Warner, Jihong Liu Sc.D., Fouzia Tarannum, James Beck, Donald Mattison

Faculty Publications

Importance Chlorhexidine mouthwash enhances treatment effects of conventional periodontal treatment, but data on chlorhexidine as a source of heterogeneity in meta-analyses assessing the treatment of maternal periodontitis in association with birth outcomes are lacking.

Objective To assess possible heterogeneity by chlorhexidine use in randomized clinical trials (RCTs) evaluating the effect of periodontal treatment (ie, scaling and root planing [SRP]) vs no treatment on birth outcomes.

Data Sources Cochrane Oral Health’s Trials Register, Cochrane Pregnancy and Childbirth’s Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE Ovid, Embase Ovid, LILACS BIREME Virtual Health Library (Latin American and Caribbean Health Science …

Association Of Chlorhexidine Use And Scaling And Root Planing With Birth Outcomes In Pregnant Individuals With Periodontitis: A Systematic Review And Meta-Analysis, Anwar T. Nerchant, Rajat Das Gupta, Maxwell Akonde, Mark Reynolds, Stephanie Smith-Warner, Jihong Liu, Fouzia Tarannum, James Beck, Donald Mattison

Faculty Publications

Importance Chlorhexidine mouthwash enhances treatment effects of conventional periodontal treatment, but data on chlorhexidine as a source of heterogeneity in meta-analyses assessing the treatment of maternal periodontitis in association with birth outcomes are lacking.

Objective To assess possible heterogeneity by chlorhexidine use in randomized clinical trials (RCTs) evaluating the effect of periodontal treatment (ie, scaling and root planing [SRP]) vs no treatment on birth outcomes.

Data Sources Cochrane Oral Health’s Trials Register, Cochrane Pregnancy and Childbirth’s Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE Ovid, Embase Ovid, LILACS BIREME Virtual Health Library (Latin American and Caribbean Health Science …

Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong

Statistical Science Theses and Dissertations

The restricted mean survival time (RMST) is a clinically meaningful summary measure in studies with survival outcomes. Statistical methods have been developed for regression analysis of RMST to investigate impacts of covariates on RMST, which is a useful alternative to the Cox regression analysis. However, existing methods for regression modeling of RMST are not applicable to left-truncated right-censored data that arise frequently in prevalent cohort studies, for which the sampling bias due to left truncation and informative censoring induced by the prevalent sampling scheme must be properly addressed. Meanwhile, statistical methods have been developed for regression modeling of the cumulative …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Carolina Rudisill, Alexander C. Mclain Ph.D.

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Caroline Rudisill, Alexander C. Mclain

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

Survival Of Epithelial Ovarian Cancer In Black Women: A Society To Cell Approach In The African American Cancer Epidemiology Study (Aaces), Joellen M. Schildkraut, Courtney Johnson, Lauren F. Dempsey, Bo Qin, Paul Terry, Maxwell Akonde, Edward S. Peters, Hannah Mandle, Michele L. Cote, Lauren Peres, Patricia Moorman, Ann G. Schwartz, Micheal Epstein, Jeffrey Marks, Melissa Bondy, Andrew B. Lawson, Anthony Alberg, Elisa V. Bandera

Faculty Publications

Purpose

The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC.

Methods

AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010–2015) are presented.

Results …

Effects Of A Behavioral Intervention On Physical Activity, Diet, And Health-Related Quality Of Life In Pregnant Women With Elevated Weight: Results Of The Hipp Randomized Controlled Trial, Sarah Wilcox Phd, Jihong Liu, Gabrielle Turner-Mcgrievy Ph.D., Rd, Alycia K. Boutte, Ellen Wingard Msph, Rd, Ld

Faculty Publications

Background

Physical activity (PA), diet, and health-related quality of life (HRQOL) are related to maternal and infant health, but interventions to improve these outcomes are needed in diverse pregnant women with elevated weight.

Methods

Health In Pregnancy and Postpartum (HIPP) was a randomized controlled trial. Women who were pregnant (N=219, 44% African American, 56% white) with overweight or obesity but otherwise healthy were randomized to a behavioral intervention grounded in Social Cognitive Theory (n=112) or to standard care (n=107). The intervention group received an in-depth counseling session, a private Facebook group, and 10 content-based …

Towards Structured Planning And Learning At The State Fisheries Agency Scale, Caleb A. Aldridge

Theses and Dissertations

Inland recreational fisheries has grown philosophically and scientifically to consider economic and sociopolitical aspects (non-biological) in addition to the biological. However, integrating biological and non-biological aspects of inland fisheries has been challenging. Thus, an opportunity exists to develop approaches and tools which operationalize planning and decision-making processes which include biological and non-biological aspects of a fishery. This dissertation expands the idea that a core set of goals and objectives is shared among and within inland fisheries agencies; that many routine operations of inland fisheries managers can be regimented or standardized; and the novel concept that current information and operations can …

Dynamics Of Redox-Driven Molecular Processes In Local And Systemic Plant Immunity, Philip Berg

Theses and Dissertations

The work here presents two main parts. In the first part, chapters 1 – 3 focus on dynamical systems modeling in plant immunity, whereas chapters 4 – 6 describe contributions to computational modeling and analysis of proteomics and genomics data. Chapter 1 investigates dynamical and biochemical patterns of reversibly oxidized cysteines (RevOxCys) during effector-triggered immunity (ETI) in Arabidopsis, examines the regulatory patterns associated with Arabidopsis thimet oligopeptidase 1 and 2’s (TOP1 and TOP2), roles in the RevOxCys events during ETI, and analyzes the redox phenotype of the top1top2 mutant. The second chapter investigates the peptidome dynamics during ETI …

Larval Ecology Of Atlantic Bluefin Tuna (Thunnus Thynnus): New Insights From Otolith Microstructure, Biotic, And Abiotic Analyses From The Gulf Of Mexico And Mediterranean Sea, Estrella Malca

All HCAS Student Capstones, Theses, and Dissertations

Atlantic bluefin tuna (ABT), Thunnus thynnus, spawn in the Gulf of Mexico (GoM) and the Mediterranean Sea (MED). Spawning occurs within narrow temporal and environmental parameters. Efforts to characterize growth of ABT in wild conditions revealed a wide range of growth variability during the early life stages. This series of studies examined potential biotic and abiotic influences of larval growth from seven ABT cohorts, and identified several key drivers of growth for this commercially valuable species. A detailed investigation of larval dynamics using otolith microstructure was conducted as follows. First, companion growth curves and stable isotope analysis from the same …

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 …