Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, 2021 Southern Methodist University
Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels
SMU Data Science Review
Understanding diagnostic tests and examining important features of novel coronavirus (COVID-19) infection are essential steps for controlling the current pandemic of 2020. In this paper, we study the relationship between clinical diagnosis and analytical features of patient blood panels from the US, Mexico, and Brazil. Our analysis confirms that among adults, the risk of severe illness from COVID-19 increases with pre-existing conditions such as diabetes and immunosuppression. Although more than eight months into pandemic, more data have become available to indicate that more young adults were getting infected. In addition, we expand on the definition of COVID-19 test and discuss ...
The Zoltar Forecast Archive, A Tool To Standardize And Store Interdisciplinary Prediction Research, 2021 University of Massachusetts Amherst
The Zoltar Forecast Archive, A Tool To Standardize And Store Interdisciplinary Prediction Research, Nicholas G. Reich, Matthew Cornell, Evan L. Ray, Katie House, Khoa Le
Biostatistics and Epidemiology Faculty Publications Series
Forecasting has emerged as an important component of informed, data-driven decision-making in a wide array of felds. We introduce a new data model for probabilistic predictions that encompasses a wide range of forecasting settings. This framework clearly defnes the constituent parts of a probabilistic forecast and proposes one approach for representing these data elements. The data model is implemented in Zoltar, a new software application that stores forecasts using the data model and provides standardized API access to the data. In one real-time case study, an instance of the Zoltar web application was used to store, provide access to, and ...
Principal Components Analysis Corrects Collider Bias In Polygenic Risk Score Effect Size Estimation, 2021 Virginia Commonwealth University
Principal Components Analysis Corrects Collider Bias In Polygenic Risk Score Effect Size Estimation, Nathaniel S. Thomas, Peter B. Barr, Fazil Aliev, Sally I. Kuo, Danielle M. Dick, Jessica E. Salvatore
Graduate Research Posters
BACKGROUND: Genome-wide polygenic scoring has emerged as a way to predict psychiatric and behavioral outcomes and identify environments that promote the expression of genetic risks. An increasing number of studies demonstrate that the effects of polygenic risk scores (PRS) may be biased by the inclusion of heritable environments as covariates when the environment is influenced by unmeasured confounding variables, an example of collider bias. Inclusion of the principal components of observed confounders as covariates may correct for the effect of unmeasured confounders.
METHODS: A simulation study was conducted to test principal components analysis (PCA) as a correction for collider bias ...
Methods For Developing A Machine Learning Framework For Precise 3d Domain Boundary Prediction At Base-Level Resolution, 2021 Virginia Commonwealth University
Methods For Developing A Machine Learning Framework For Precise 3d Domain Boundary Prediction At Base-Level Resolution, Spiro C. Stilianoudakis
Theses and Dissertations
High-throughput chromosome conformation capture technology (Hi-C) has revealed extensive DNA looping and folding into discrete 3D domains. These include Topologically Associating Domains (TADs) and chromatin loops, the 3D domains critical for cellular processes like gene regulation and cell differentiation. The relatively low resolution of Hi-C data (regions of several kilobases in size) prevents precise mapping of domain boundaries by conventional TAD/loop-callers. However, high resolution genomic annotations associated with boundaries, such as CTCF and members of cohesin complex, suggest a computational approach for precise location of domain boundaries.
We developed preciseTAD, an optimized machine learning framework that leverages a random ...
A Bayesian Hierarchical Mixture Model With Continuous-Time Markov Chains To Capture Bumblebee Foraging Behavior, Max Thrush Hukill
The standard statistical methodology for analyzing complex case-control studies in ethology is often limited by approaches that force researchers to model distinct aspects of biological processes in a piecemeal, disjointed fashion. By developing a hierarchical Bayesian model, this work demonstrates that statistical inference in this context can be done using a single coherent framework. To do this, we construct a continuous-time Markov chain (CTMC) to model bumblebee foraging behavior. To connect the experimental design with the CTMC, we employ a mixture model controlled by a logistic regression on the two-factor design matrix. We then show how to infer these model ...
Piecewise Linear Regression For Leaf Appearance Rate Data, 2021 Iowa State University
Piecewise Linear Regression For Leaf Appearance Rate Data, Lin Quan
Segmented regression models are generalization of linear and generalized linear models that replace a linear predictor with a piecewise linear predictor. Breakpoints where the piecewise linear predictor changes slope are unknown and estimated from data. We use segmented regression to model the relationship between the number of plant leaves and thermal time for hundreds of maize genotypes. Slope estimates from fitted segmented regression models provide estimates of leaf appearance rate (LAR) for each genotype. Estimates of breakpoints provide insight into developmental time points when changes in LAR occur for each genotype. We compare inferences about slopes and breakpoints obtained from ...
An Updated Method For Correcting Batch Effect, 2021 Iowa State University
An Updated Method For Correcting Batch Effect, Yonghui Huo
I propose a novel variation (Pro-SVA) on iteratively reweighted surrogate variable analysis (IRW-SVA) for detecting and measuring batch effects in high dimensional gene expression data. Specifically, I propose to use the matrix-free high dimensional factor analysis (HDFA) algorithm instead of singular value decomposition (SVD) in the IRW-SVA iterations. HDFA efficiently provides the maximum likelihood estimates of the error variances and batch loadings, which can subsequently be used to estimate the batch factors. To evaluate the performance of Pro-SVA, I simulated 100 samples of 1,000 genes with batch effects and (1) no biological effects, (2) biological effects for half ...
A Model For Inhalation Of Infectious Aerosol Contaminants In An Aircraft Passenger Cabin, 2021 Vector Vantage LLC
A Model For Inhalation Of Infectious Aerosol Contaminants In An Aircraft Passenger Cabin, Bert A. Silich
International Journal of Aviation, Aeronautics, and Aerospace
Aerosol contamination of an aircraft cabin by infectious passengers is a concern of passengers, aircrew and the aviation industry. This may be especially important during a pandemic, such as COVID-19, where the full extent of aerosol transmission is not well understood. A statistical method to determine the number of infectious passengers on board along with a mathematical model estimating the contaminant concentration of aerosols in the cabin and the number of inhaled infectious particles by passengers is presented. An example is used to demonstrated how the results can be estimated during normal operations and emergency conditions with malfunctions of the ...
The Causes And Control Measures Of Extended Spectrum Beta-Lactamase Producing Enterobacteriaceae In Long-Term Care Facilities, Ismaila Olatunji Sule
Walden Dissertations and Doctoral Studies
Due to extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE), infections among residents are increasing in long-term care facilities (LTCFs), resulting in high rate of morbidity and healthcare costs. ESBL-PE resists empirical antibiotics and reduces treatment options, and a designated infection control team is unavailable to prevent the prevalence of the disease. Ecological theory guided this study. A systematic review and meta-analysis were conducted to characterize the causes of ESBL-PE and evaluate the infection control strategies within LTCFs. Multiple regression analysis (MRA) was included as supplementary statistical analysis to identify relationships between LTCFs, geographical locations, infection control measures (ICMs), and ESBL-PE. A systematic search ...
Dach1 Mutation Frequency In Endometrial Cancer Is Associated With High Tumor Mutation Burden, 2020 University of Kentucky
Dach1 Mutation Frequency In Endometrial Cancer Is Associated With High Tumor Mutation Burden, Mckayla J. Riggs, Nan Lin, Chi Wang, Dava W. Piecoro, Rachel W. Miller, Oliver A. Hampton, Mahadev Rao, Frederick R. Ueland, Jill M. Kolesar
Obstetrics and Gynecology Faculty Publications
OBJECTIVE: DACH1 is a transcriptional repressor and tumor suppressor gene frequently mutated in melanoma, bladder, and prostate cancer. Loss of DACH1 expression is associated with poor prognostic features and reduced overall survival in uterine cancer. In this study, we utilized the Oncology Research Information Exchange Network (ORIEN) Avatar database to determine the frequency of DACH1 mutations in patients with endometrial cancer in our Kentucky population.
METHODS: We obtained clinical and genomic data for 65 patients with endometrial cancer from the Markey Cancer Center (MCC). We examined the clinical attributes of the cancers by DACH1 status by comparing whole-exome sequencing (WES ...
Bayesian Semi-Supervised Keyphrase Extraction And Jackknife Empirical Likelihood For Assessing Heterogeneity In Meta-Analysis, 2020 Southern Methodist University
Bayesian Semi-Supervised Keyphrase Extraction And Jackknife Empirical Likelihood For Assessing Heterogeneity In Meta-Analysis, Guanshen Wang
Statistical Science Theses and Dissertations
This dissertation investigates: (1) A Bayesian Semi-supervised Approach to Keyphrase Extraction with Only Positive and Unlabeled Data, (2) Jackknife Empirical Likelihood Confidence Intervals for Assessing Heterogeneity in Meta-analysis of Rare Binary Events.
In the big data era, people are blessed with a huge amount of information. However, the availability of information may also pose great challenges. One big challenge is how to extract useful yet succinct information in an automated fashion. As one of the first few efforts, keyphrase extraction methods summarize an article by identifying a list of keyphrases. Many existing keyphrase extraction methods focus on the unsupervised setting ...
Cellphone Laws And Teens' Calling While Driving: Analysis Of Repeated Cross-Sectional Surveys In 2013, 2015, 2017, And 2019, 2020 The Ohio State University
Cellphone Laws And Teens' Calling While Driving: Analysis Of Repeated Cross-Sectional Surveys In 2013, 2015, 2017, And 2019, Li Li, Caitlin N. Pope, Rebecca R. Andridge, Julie K. Bower, Guoqing Hu, Motao Zhu
Graduate Center for Gerontology Faculty Publications
BACKGROUND: Distracted driving among teens is a public health and safety concern. Most states in the U.S. have sought to restrict cellphone use while driving by enacting laws. This study examines the difference in prevalence of self-reported calling while driving (CWD) between states with different cellphone bans.
METHODS: Demographics and CWD data were extracted from state Youth Risk Behavior Surveys (YRBS) from 14 states in 2013, 2015, 2017, and 2019. The state YRBS is conducted every 2 years with a representative sample of 9th through 12th grade students attending public school. States were grouped by type of cellphone law ...
Uganda As A Role Model For Pandemic Containment In Africa, 2020 Aga Khan University
Uganda As A Role Model For Pandemic Containment In Africa, Ahmed M. Sarki, Alex Ezeh, Saverio Stranges
Epidemiology and Biostatistics Publications
No abstract provided.
Conditional Distance Correlation Test For Gene Expression Level, Dna Methylation Level And Copy Number, 2020 University of Arkansas, Fayetteville
Conditional Distance Correlation Test For Gene Expression Level, Dna Methylation Level And Copy Number, Shanshan Zhang
Theses and Dissertations
Over the past years, efforts have been devoted to the genome-wide analysis of genetic and epigenetic profiles to better understand the underlying biological mechanisms of complex diseases such as cancer. It is of great importance to unravel the complex dependence structure between biological factors, and many conditional dependence tests have been developed to meet this need. The traditional partial correlation method can only capture the linear partial correlation, but not the nonlinear correlation. To overcome this limitation, we propose to use the innovative conditional distance correlation (CDC), which measures the conditional dependence between random vectors and detect nonlinear relations. In ...
Gene Set Testing By Distance Correlation, 2020 University of Arkansas, Fayetteville
Gene Set Testing By Distance Correlation, Sho-Hsien Su
Theses and Dissertations
Pathways are the functional building blocks of complex diseases such as cancers. Pathway-level studies may provide insights on some important biological processes. Gene set test is an important tool to study the differential expression of a gene set between two groups, e.g., cancer vs normal. The differential expression of a gene set could be due to the difference in mean, variability, or both. However, most existing gene set tests only target the mean difference but overlook other types of differential expression. In this thesis, we propose to use the recently developed distance correlation for gene set testing. To assess ...
Direct Questioning Of Sensitive Topics In Public Health Studies: A Simulation Study, 2020 LSU Health Sciences Center, School of Public Health, Biostatistics Program
Direct Questioning Of Sensitive Topics In Public Health Studies: A Simulation Study, Jessica K. Fox, Evrim Oral
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Evidence Of Nickel And Other Trace Elements And Their Relationship To Clinical Findings In Acute Mesoamerican Nephropathy: A Case-Control Analysis, Rebecca S. B. Fischer, Jason M. Unrine, Chandan Vangala, Wayne T. Sanderson, Sreedhar Mandayam, Kristy O. Murray
Plant and Soil Sciences Faculty Publications
BACKGROUND: Although there are several hypothesized etiologies of Mesoamerican Nephropathy (MeN), evidence has not yet pointed to the underlying cause. Exposure to various trace elements can cause the clinical features observed in MeN.
METHODS AND FINDINGS: We measured 15 trace elements, including heavy metals, in renal case-patients (n = 18) and healthy controls (n = 36) in a MeN high-risk region of Nicaragua. Toenails clippings from study participants were analyzed using inductively coupled plasma mass spectrometry. A case-control analysis was performed, and concentrations were also analyzed over participant characteristics and clinical parameters. Nickel (Ni) concentrations were significantly higher in toenails from cases ...
Implementation And Sustainment Of A Statewide Telemedicine Diabetic Retinopathy Screening Network For Federally Designated Safety-Net Clinics, Ana Bastos De Carvalho, S. Lee Ware, Feitong Lei, Heather M. Bush, Robert Sprang, Eric B. Higgins
Ophthalmology and Visual Science Faculty Publications
CONTEXT: Diabetic retinopathy (DR) is the leading cause of incident blindness among working-age adults in the United States. Federally designated safety-net clinics (FDSC) often serve as point-of-contact for patients least likely to receive recommended DR screenings, creating opportunity for targeted interventions to increase screening access and compliance.
STUDY DESIGN AND METHODS: With such a goal, we implemented and assessed the longitudinal performance of an FDSC-based telemedicine DR screening (TDRS) network of 22 clinical sites providing nonmydriatic fundus photography with remote interpretation and reporting. Retrospective analysis of patient encounters between February 2014 and January 2019 was performed to assess rates of ...
Effect Of Renin-Angiotensin System Inhibitors On Acute Kidney Injury Among Patients Undergoing Cardiac Surgery: A Review And Meta-Analysis, 2020 National University of Singapore
Effect Of Renin-Angiotensin System Inhibitors On Acute Kidney Injury Among Patients Undergoing Cardiac Surgery: A Review And Meta-Analysis, Han Zhou, Jingui Xie, Zhichao Zheng, Oon Cheong Ooi, Haidong Luo
Research Collection Lee Kong Chian School Of Business
Acute kidney injury (AKI) is a frequent complication of cardiac surgery, which can lead to higher mortality and long-term renal function impairment. The effect of perioperative renin-angiotensin system inhibitors (RASi) therapy on AKI incidence in patients undergoing cardiac surgery remains controversial. We reviewed related studies in PubMed, Scopus, and Cochrane Library from inception to February 2020. Two randomized controlled trials and 21 cohort studies were included in the meta-analysis, involving 76,321 participants. The pooled odds ratio and 95% confidence interval were calculated using the DerSimonian and Laird random-effects model. The results showed no significant association between perioperative RASi therapy ...
The Use Of Penalized Regression Analysis To Identify County-Level Demographic And Socioeconomic Variables Predictive Of Increased Covid-19 Cumulative Case Rates In The State Of Georgia, 2020 Georgia Southern University, Jiann-Ping Hsu College of Public Health
The Use Of Penalized Regression Analysis To Identify County-Level Demographic And Socioeconomic Variables Predictive Of Increased Covid-19 Cumulative Case Rates In The State Of Georgia, Holly L. Richmond, Joana Tome, Haresh Rochani, Isaac Chun-Hai Fung, Gulzar H. Shah, Jessica S. Schwind
Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications
Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables ...