Digital Commons Network^™

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Improving Computation For Hierarchical Bayesian Spatial Gaussian Mixture Models With Application To The Analysis Of Thz Image Of Breast Tumor, Jean Remy Habimana

Graduate Theses and Dissertations

In the first chapter of this dissertation we give a brief introduction to Markov chain Monte Carlo methods (MCMC) and their application in Bayesian inference. In particular, we discuss the Metropolis-Hastings and conjugate Gibbs algorithms and explore the computational underpinnings of these methods. The second chapter discusses how to incorporate spatial autocorrelation in linear a regression model with an emphasis on the computational framework for estimating the spatial correlation patterns.

The third chapter starts with an overview of Gaussian mixture models (GMMs). However, because in the GMM framework the observations are assumed to be independent, GMMs are less effective when …

Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura

Mathematics & Statistics ETDs

This study compared the performance of machine learning models in classifying COVID-19 patients using exhaled breath signals and simulated datasets. Ground truth classification was determined by the gold standard Polymerase Chain Reaction (PCR) test results. A residual bootstrapped method generated the simulated datasets by fitting signal data to Autoregressive Moving Average (ARMA) models. Classification models included neural networks, k-nearest neighbors, naïve Bayes, random forest, and support vector machines. A Recursive Feature Elimination (RFE) study was performed to determine if reducing signal features would improve the classification models performance using Gini Importance scoring for the two classes. The top 25% of …

Robust Uncertainty Quantification With Analysis Of Error In Standard And Non-Standard Quantities Of Interest, Zachary Stevens

Mathematics & Statistics ETDs

This thesis derives two Uncertainty Quantification (UQ) methods for differential equations that depend on random parameters: (\textbf{i}) error bounds for a computed cumulative distribution function (\textbf{ii}) a multi-level Monte Carlo (MLMC) algorithm with adaptively refined meshes and accurately computed stopping-criteria. Both UQ approaches utilize adjoint-based \textit{a posteriori} error analysis in order to accurately estimate the error in samples of numerically approximated quantities of interest. The adaptive MLMC algorithm developed in this thesis relies on the adjoint-based error analysis to adaptively create meshes and accurately monitor a stopping criteria. This is in contrast to classical MLMC algorithms which employ either a …

Semiparametric Estimation With Clustered Right Censored Data Via Multivariate Gaussian Random Fields, Fathima Zahra Sainul Abdeen

Doctoral Dissertations

Consider a fixed number of clustered areas identified by their geographical coordinate that are monitored for the occurrences of an event such as pandemic, epidemic, migration to name a few. Data collected on units at all areas include time varying covariates and other environmental factors that may affect event occurrences. The event times in every area can be independent. They can also be correlated with correlation between two units induced by an unobservable frailty. In both cases, the collected data is considered pairwise to account for spatial correlation between all pair of areas. The pairwise right censored data is probit-transformed …

Changes Overtime In Perinatal Management And Outcomes Of Extremely Preterm Infants In One Tertiary Care Romanian Center, Diana Ungureanu, Nansi Boghossian, Laura Mihaela Suciu

Faculty Publications

Background and Objectives: Extremely preterm infants were at increased risk of mortality and morbidity. The purpose of this study was to: (1) examine changes over time in perinatal management, mortality, and major neonatal morbidities among infants born at 25⁰–28⁶ weeks’ gestational age and cared for at one Romanian tertiary care unit and (2) compare the differences with available international data. Material and Methods: This study consisted of infants born at 25⁰–28⁶ weeks in one tertiary neonatal academic center in Romania during two 4-year periods (2007–2010 and 2015–2018). Major morbidities were defined as any of …

Random Walks In The Quarter Plane: Solvable Models With An Analytical Approach, Harshita Bali, Enrico Au-Yeung

DePaul Discoveries

Initially, an urn contains 3 blue balls and 1 red ball. A ball is randomly chosen from the urn. The ball is returned to the urn, together with one additional ball of the same type (red or blue). When the urn has twenty balls in it, what is the probability that exactly ten balls are blue? This is a model for a random process. This urn model has been extended in various ways and we consider some of these generalizations. Urn models can be formulated as random walks in the quarter plane. Our findings indicate that for a specific type …

Spotted Fever Group Rickettsioses In Central America: The Research And Public Health Disparity Among Socioeconomic Lines, Kyndall C. Dye-Braumuller, Marvin S. Rodriguez Aquino, Stella C.W. Self, Mufaro Kanyangarara, Melissa Nolan Ph.D., Mph

Faculty Publications

Tick-borne diseases including rickettsial diseases are increasing in incidence worldwide. Many rickettsial pathogens can cause disease which is commonly underdiagnosed and underreported; Rickettsia pathogens in the spotted fever group (SFGR) are thus classified as neglected bacterial pathogens. The Central American region shoulders a large proportion of the global neglected disease burden; however, little is known regarding SFGR disease here. Although development varies, four of the seven countries in this region have both the highest poverty rates and SFGR disease burdens (El Salvador, Honduras, Guatemala, and Nicaragua), compared to Belize, Panama, and Costa Rica. Utilizing the Human Development Index (HDI), we …

Joint Models For Repeated Measured, Non-Normally Distributed Multilevel Data, Weiwei He

USF Tampa Graduate Theses and Dissertations

Clinical trials have tended to collect both survival information and longitudinal biomarkers, as well as other covariates. In order to better assess the severity of diverse diseases, we need to collect various longitudinal outcomes. Furthermore, longitudinal data could consist of a number of different measurements of varying types. The multilevel item response theory (MLIRT) model has been widely used in several fields such as public health and health sciences for multivariate longitudinal outcomes. Joint models combining the longitudinal and survival processes, as well as the relation between them, have been developed to minimize bias and improve the efficiency of estimates. …

Capturing The Pool Dilution Effect In Group Testing Regression: A Bayesian Approach, Stella Self Ph.D., Ms, Christopher Mcmahan, Stefani Mokalled

Faculty Publications

Group (pooled) testing is becoming a popular strategy for screening large populations for infectious diseases. This popularity is owed to the cost savings that can be realized through implementing group testing methods. These methods involve physically combining biomaterial (eg, saliva, blood, urine) collected on individuals into pooled specimens which are tested for an infection of interest. Through testing these pooled specimens, group testing methods reduce the cost of diagnosing all individuals under study by reducing the number of tests performed. Even though group testing offers substantial cost reductions, some practitioners are hesitant to adopt group testing methods due to the …

The Impact Of Service Dogs On Objective And Perceived Sleep Quality For Veterans With Ptsd, Madhuri Vempati, Elise A. Miller, Sarah C. Leighton, Leanne O. Nieforth, Marguerite O’Haire

Discovery Undergraduate Interdisciplinary Research Internship

One in four post-9/11 veterans (Fulton et al., 2015) have been diagnosed with posttraumatic stress disorder (PTSD), facing sleep disruptions as one of their most common symptoms. Service dogs have become an increasingly popular complementary intervention and anecdotes suggest they may impact sleep for veterans with PTSD. There is a need for empirical investigation into these claims through measurement and analysis of sleep quality.

The purpose of this study was to longitudinally investigate the impact of service dogs on sleep quality through both objective and subjective measures.

Participants in the treatment group (n=92) received a service dog after baseline, while …

Concerns With Taking The Covid-19 Vaccine, Kaela Bellamy, Robert S. Keyser

The Kennesaw Journal of Undergraduate Research

This IRB-approved descriptive study provides an overview of the concerns associated with receiving a COVID-19 vaccination within the Kennesaw State University community, an R2 university with over 41,000 students, and uses a survey to provide insight into how students, faculty, staff, and administrators are responding to the vaccinations for COVID-19, both available and unavailable, and their preferences. Our research findings indicate that: 1) Most of the population at Kennesaw State University intends to receive the vaccine, regardless of their concerns; 2) The majority of the participants who are either employed or provided an education by Kennesaw State University plan to …

Spatio-Temporal Models Of Infectious Disease With High Rates Of Asymptomatic Transmission, Aminur Rahman, Angela Peace, Ramesh Kesawan, Souparno Ghosh

Department of Statistics: Faculty Publications

The surprisingly mercurial Covid-19 pandemic has highlighted the need to not only accelerate research on infectious disease, but to also study them using novel techniques and perspectives. A major contributor to the dificulty of containing the current pandemic is due to the highly asymptomatic nature of the disease. In this investigation, we develop a modeling framework to study the spatio-temporal evolution of diseases with high rates of asymptomatic transmission, and we apply this framework to a hypothetical country with mathematically tractable geography; namely, square counties uniformly organized into a rectangle. We first derive a model for the temporal dynamics of …

Respiratory, Neurological And Other Health Outcomes Among Plastic Factory Workers In Gazipur, Bangladesh, Shobhan Das, Md. Masudur Rahman, Asmaul Husna, Margia Akter, Md. Matiur Rahaman, Md. Taohidul Islam, Md. Jamal Uddin, Atin Adhikari

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Background: Approximately three thousand plastic goods manufacturing factories (PGMF) are currently operating in Bangladesh involving numerous workers. Associated health problems of these workers are largely unknown. The key objectives of the current study were identifying plastic chemical exposures related health outcomes in these workers and comparing these outcomes before and after their joining in PGMFs. In addition, we aimed to investigate the relationships between work duration and the prevalence of health ailments among workers.

Method: A cross-sectional study was carried out among factory workers (n=405) at six PGMFs in Gazipur district in Bangladesh. A simple random sampling method had been …

Effect Of Phylogeny Misestimation On Estimating Trait Evolution Parameters, Tabytha Ariel Perez

Mathematics & Statistics ETDs

Biologists are interested in estimating trait evolution models from phylogenies. However, phylogenies are imperfectly estimated, generally from DNA sequence data. In this study, true phylogenies are simulated to understand whether errors in phylogeny estimation affect inference of the trait evolution model. Given the tree, DNA sequences as well as traits are then simulated from the true phylogeny; both are simulated independently from the other. After the simulation, the DNA sequences were used to estimate trees using the UPGMA method without utilizing the trait information. The estimated trees combined with the traits are used to infer the evolutionary trait models, specifically …

Consequences Of Gulf Of Mexico Estuarine Tropical Cyclone Disturbance Regimes For Fish Assemblage Dynamics Conditionally Depend On Life-History Traits And Niche Characteristics, Stephen Edward Potts

LSU Doctoral Dissertations

Tropical cyclones (TC) are intense, localized disturbances that can potentially cause extensive damage to ecosystems. This dissertation is motivated by a need for interdisciplinary study of TC-ecosystem dynamics with applications to ecology, geography, and analytical methodology. I explore concept linkages between TC dynamics and ecosystems to characterize TC-ecosystem relationships as ecological disturbance regimes. This dissertation tests hypotheses and relationships of TC effects on estuarine fish assemblages in the north-western Gulf of Mexico. I explore concepts in TC-ecosystem relationships to link biotic dynamics with physical disturbance.

In Chapter 2, I compared spatial performance of generalized linear models (GLMs) and generalized additive …

Impact Of Oil And A Tropical Cyclone On An Omnivore And Herbivore Population In Salt Marshes Of Louisiana, Hannah K. Gordon

LSU Master's Theses

Terrestrial arthropods are the ideal ecological indicators for the health of a salt marsh. Salt marshes are under extreme continuous stressors including climate change, land loss, oil spills, and tropical cyclones. Such stressors impact trophic and species level interactions, food resources, dispersal and population size of insects. In the present study, we collected terrestrial arthropods from eleven sites around Barataria Bay, five sites were oiled and five sites were unoiled, to determine the impact of the redistribution of oil from the Deepwater Horizon oil spill. Site C6 was excluded from the oiled and unoiled data because it was in close …

Talking About Statistical Significance In Numeracy, Nathan D. Grawe, Gizem Karaali

Numeracy

In recent years, much debate has surrounded the potential for audiences to be mislead by several common practices when reporting statistical significance tests. Two editors of Numeracy share the journals perspectives on these questions. As an interdisciplinary journal, we recognize and honor the genre differences represented by our authors and audience members. As a consequence, the journal is open to many practices. Still, we acknowledge the concerns raised by the American Statistical Association and others and encourage authors to write with care and clarity, however results may be represented.

Heterogeneity Of Gene Trees, Jonathan Nenye Odumegwu Unm

Mathematics & Statistics ETDs

Multilocus phylogenetic studies often show a high degree of gene tree heterogeneity —gene trees that have different topologies from each other as well as from the species tree topology. In some cases, this can lead to studies with hundreds of loci having distinct gene tree topologies. The degree of heterogeneity is expected to increase when there is a high degree of incomplete lineage sorting due to short branches (as measured in coalescent units) in the species tree. Other potential sources of heterogeneity include other biological processes such as introgression, recombination within genes, ancestral population structure, gene duplication and loss, and …

Reply To Response By Fbi Laboratory Filed In Illinois V. Winfield And Affidavit By Biederman Et Al. (2022) Filed In Us V. Kaevon Sutton (2018 Cf1 009709), Susan Vanderplas, Kori Khan, Heike Hofmann, Alicia Carriquiry

Department of Statistics: Faculty Publications

1 Preliminaries

1.1 Scope

The aim of this document is to respond to issues raised in Federal Bureau of Investigation¹ and Alex Biedermann, Bruce Budowle & Christophe Champod.²

1.2 Conflict of Interest

We are statisticians employed at public institutions of higher education (Iowa State University and University of Nebraska, Lincoln) and have not been paid for our time or expertise when preparing either this response or the original affidavit.³ We provide this information as a public service and as scientists and researchers in this area.

1.3 Organization

The rest of the document precedes as follows: we begin …

Derivation And Analysis Of A Discrete Predator–Prey Model, Sabrina H. Streipert, Gail S.K. Wolkowicz, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

We derive a discrete predator–prey model from first principles, assuming that the prey population grows to carrying capacity in the absence of predators and that the predator population requires prey in order to grow. The proposed derivation method exploits a technique known from economics that describes the relationship between continuous and discrete compounding of bonds. We extend standard phase plane analysis by introducing the next iterate root-curve associated with the nontrivial prey nullcline. Using this curve in combination with the nullclines and direction field, we show that the prey-only equilibrium is globally asymptotic stability if the prey consumption-energy rate of …

The Prevalence And Impact Of Adolescent Hospitalization To Adult Psychiatric Units., Samantha Mcrae, Jordan Edwards, Kathy N Speechley, Javeed Sukhera, Guangyong Zou, Kelly K. Anderson

Epidemiology and Biostatistics Publications

BACKGROUND: With increasing psychiatric hospitalizations among adolescents and constrained hospital resources, there are times when youth are hospitalized in adult inpatient psychiatry units. Evidence on the prevalence of this practice and associated impacts is lacking.

AIMS: We sought to explore the prevalence, determinants, and outcomes related to the hospitalization of adolescents aged 12-17 years on adult inpatient psychiatry units in Ontario.

METHODS: Using health administrative data, we constructed a cohort of adolescents with an inpatient psychiatric admission in Ontario (2007-2011). We classified adolescents as having an admission to an adult psychiatry unit or to other inpatient units. Multivariable regression models …

Quality And Transparency, Christopher J. Smiley Dds

The Journal of the Michigan Dental Association

In a recent JDR Clinical & Translational Research report, the American Dental Association's clinical practice guidelines (CPGs) were determined to offer high-quality guidance for the dental profession. The study employed the AGREE II tool to validate the ADA's guidelines’ methodological rigor and transparency, ensuring their quality. This external review is promising for the profession, as it indicates that the ADA has developed reliable CPGs that support advocacy and implementation. However, the article raises questions about consumer-targeted quality scores for dentist providers, such as DentaQual by P&R Dental Strategies LLC. It suggests that for such scoring systems to be credible, they …

Modified Em Algorithm In Smcure Package Based On Proportional Hazards Mixture Cure Model With Offset Terms, Jiaying Yi

Theses and Dissertations

Mixture cure model is a useful method of survival analysis for population including cured proportion and uncured proportion. The R package SMCURE applies EM algorithm to estimate the coefficients of covariates in the mixture cure model. Although an offset term is specified in the SMCURE statement, the offset term is not appropriately handled in the algorithm. This thesis aims to adjust the EM algorithm for the proportional hazards mixture cure model in the SMCURE package. In addition, the offset term can be specified separately in the incidence part or the latency part. The numerical experiments include simulation study and real …

Statistical Methods For Analyzing Dependence Structures With Applications In Single-Cell Experiments, Zhen Yang

Theses and Dissertations

This dissertation focuses on studying methods in dependence structure analysis. In particular, it consists of two topics: (1) modeling dynamic correlation in zero-inflated bivariate count data; and (2) gene co-expression latent factor analysis for cell-type clustering.

In Chapter 2, a zero-inflated negative binomial model for analyzing the dynamic correlation in zero-inflated bivariate count data is proposed. Interactions between biological molecules in a cell are tightly coordinated and often highly dynamic. As a result of these varying signaling activities, changes in gene co-expression patterns could often be observed. The advancements in next-generation sequencing tech-nologies bring new statistical challenges for studying these …

Statistical Methods For Analyzing Multi-Omics Data: Dependence Structure And Missing Values, Wenda Zhang

Theses and Dissertations

The advancements in high-throughput technologies have made it possible to generate a huge number of "omics'' data, including genomics, proteomics, transcriptomics, epigenomics, metabolomics, and microbiomics. Combining multiple data sources and performing joint analyses with all available information and the phenotypic outcome can reflect various aspects in complex biological systems, such as revealing regulation processes, discovering novel associations between biological entities, and identifying relevant biomarkers for certain diseases or phenotypic outcomes. This dissertation focuses on developing statistical models for analyzing multi-omics data. It is comprised of three topics: (1) integrative analysis for multi-omics data with missing observations in intermediate variables; (2) …

Complex Functional Joint Models For Longitudinal Electronic Health Record, Siyuan Guo

Theses and Dissertations

Longitudinal measurements are important components in electronic health record (EHR) data. In practice, using longitudinal EHR history is expected to improve the estimation or prediction performance when studying some outcomes of interest, such as binary outcome or time to event outcome. However, the longitudinal observations in EHR data is complex due to irregular and sparse EHR visits. Therefore, modelling longitudinal data and further incorporating them with different types of outcomes is challenge. In this dissertation, we aim to develop methodology to first, describe the pattern of the longitudinal predictors with continuous or binary observations, and second, model the longitudinal predictors …

Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …

Genomic Prediction Accuracy Of Stripe Rust In Six Spring Wheat Populations By Modeling Genotype By Environment Interaction, Kassa Semagn, Muhammad Iqbal, Diego Jarquin, Harpinder Randhawa, Reem Aboukhaddour, Reka Howard, Izabela Ciechanowska, Momna Farzand, Raman Dhariwal, Colin W. Hiebert, Amidou N’Diaye, Curtis Pozniak, Dean Spaner

Department of Statistics: Faculty Publications

Some previous studies have assessed the predictive ability of genome-wide selection on stripe (yellow) rust resistance in wheat, but the effect of genotype by environment interaction (GEI) in prediction accuracies has not been well studied in diverse genetic backgrounds. Here, we compared the predictive ability of a model based on phenotypic data only (M1), the main effect of phenotype and molecular markers (M2), and a model that incorporated GEI (M3) using three cross-validations (CV1, CV2, and CV0) scenarios of interest to breeders in six spring wheat populations. Each population was evaluated at three to eight field nurseries and genotyped with …

Numerical Solutions To The Robin Inverse Problem With Nonnegativity Constraints, Weifu Fang, Fu-Rong Lin

Mathematics and Statistics Faculty Publications

We present iterative numerical methods for solving the inverse problem of recovering the nonnegative Robin coefficient from partial boundary measurement of the solution to the Laplace equation. Based on the boundary integral equation formulation of the problem, nonnegativity constraints in the form of a penalty term are incorporated conveniently into least-squares iteration schemes for solving the inverse problem. Numerical implementation and examples are presented to illustrate the effectiveness of this strategy in improving recovery results.