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Articles 1 - 28 of 28
Full-Text Articles in Probability
Using Camera-Based Unmarked Spatial Capture-Recapture Modeling To Estimate Reintroduced Elk (Cervus Canadensis) Population Parameters And Distribution In Southeastern Kentucky, Claire Marie Muia
Theses and Dissertations--Forestry and Natural Resources
Estimation of population parameters is important for wildlife management decisions. Elk reintroduced to southeastern Kentucky experienced early irruptive population growth and are currently monitored using a statewide harvest-based statistical population reconstruction model (SPR) across the Kentucky Elk Restoration Zone (KERZ). Because the SPR model is spatially coarse and difficult to scale to the smaller management units comprising the KERZ, we conducted a spatially explicit capture-recapture study using a clustered camera-trapping array deployed for 10 weeks from June–August 2024 to estimate elk population parameters within Management Unit 4. Due to a lack of resights of GPS-marked elk, population parameters were estimated …
Beyond The Lace Index: Benchmarking Machine Learning Architectures And Explaining 30-Day Hospital Readmission Risk With Shap Analysis, Carl E. Hughes Iii
Beyond The Lace Index: Benchmarking Machine Learning Architectures And Explaining 30-Day Hospital Readmission Risk With Shap Analysis, Carl E. Hughes Iii
Williams Honors College, Honors Research Projects
Unplanned 30-day hospital readmission remains a fundamental challenge in US healthcare, associated with increased risk to patient recovery and representing an estimated $52.4 billion in annual expenses (Beauvais et al., 2022). While the rigorously validated LACE index serves as the clinical standard for readmission modeling, its linear structure and four explanatory variables lack the complexity to capture the high-dimensional and interactive nature of patient risk. This study utilizes an admission granularity level cohort of the MIMIC-IV database to develop and compare machine learning architectures against the baseline LACE index. Due to the imbalanced prevalence of readmission, the penalized logistic regression, …
Evaluating Novel Approaches For Improving Anadromous Fish Passage In Coastal Rivers, Aaron Bunch
Evaluating Novel Approaches For Improving Anadromous Fish Passage In Coastal Rivers, Aaron Bunch
All Dissertations
Few of the world's rivers remain free-flowing for over 1000 km, significantly impacting anadromous fish populations due to dam-induced habitat fragmentation. Three partial migration barriers (low-head dams) on North Carolina's Cape Fear River (USA)—lock and dam 1 (LD1), lock and dam 2 (LD2), and lock and dam 3 (LD3)—impact American shad Alosa sapidissima, Atlantic sturgeon Acipenser oxyrinchus oxyrinchus, and striped bass Morone saxatilis populations. Mitigation strategies to pass fish upstream have included conservation locking, nature-like fishway construction, and environmental flows (e-flows). This study introduced a novel e-flow (dam submergence flow), tested acoustic double-tagging techniques for tracking American …
Latent Classification Of Multi-Model Non-Homogeneous Continuous-Time Markov Chains, Joonha Chang
Latent Classification Of Multi-Model Non-Homogeneous Continuous-Time Markov Chains, Joonha Chang
Dissertations and Theses (Open Access)
The continuous-time Markov chain (CTMC) model and latent clustering models are commonly used to study longitudinal measures of categorical outcomes. Because of its simple but powerful Markovian property, CTMC models have been widely used in medical and public health researches. Due to limitations in the standard CTMC model, there have been some studies on non-homogeneous continuous-time Markov chain (NH-CTMC) that utilized time-dependent rates, but the progresses have been limited. NH-CTMC can be more powerful than CTMC by its default nature of time-dependent rate that can be fitted to a wider range of applications in medical studies. In this study, we …
Coral Scar Investigation: An Application Of Machine Learning And Computational Biology Methods To Understand Coral Holobiont Response To Various Tissue Loss Diseases, Emily W. Van Buren
Coral Scar Investigation: An Application Of Machine Learning And Computational Biology Methods To Understand Coral Holobiont Response To Various Tissue Loss Diseases, Emily W. Van Buren
Biology Dissertations - Archive
Coral disease is one of the biggest challenges facing coral reefs that actively changes biodiversity resulting in coral decline. With the rising threat of diseases, corals require biomarkers that reflect the immune systems and differences between common coral tissue loss diseases to best assist in coral restoration efforts. To obtain these biomarkers, my dissertation leverages two previously published datasets from two tissue loss disease exposure studies to investigate genes that are relevant for coral immune pathways, disease susceptibility, and classification between the diseases. In Chapter 2, I use comparative computational biology tools and protein assays to identify the melanin cascade …
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Theses and Dissertations (Comprehensive)
The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Aspects Of Stochastic Geometric Mechanics In Molecular Biophysics, David Frost
Aspects Of Stochastic Geometric Mechanics In Molecular Biophysics, David Frost
All Dissertations
In confocal single-molecule FRET experiments, the joint distribution of FRET efficiency and donor lifetime distribution can reveal underlying molecular conformational dynamics via deviation from their theoretical Forster relationship. This shift is referred to as a dynamic shift. In this study, we investigate the influence of the free energy landscape in protein conformational dynamics on the dynamic shift by simulation of the associated continuum reaction coordinate Langevin dynamics, yielding a deeper understanding of the dynamic and structural information in the joint FRET efficiency and donor lifetime distribution. We develop novel Langevin models for the dye linker dynamics, including rotational dynamics, based …
A Novel Family Of Chain Binomial Models To Investigate Correlated Vaccination And Infection Rates In Sveirs Epidemic Dynamics, Divine Wanduku
A Novel Family Of Chain Binomial Models To Investigate Correlated Vaccination And Infection Rates In Sveirs Epidemic Dynamics, Divine Wanduku
Biology and Medicine Through Mathematics Conference
No abstract provided.
Utilizing Markov Chains To Estimate Allele Progression Through Generations, Ronit Gandhi
Utilizing Markov Chains To Estimate Allele Progression Through Generations, Ronit Gandhi
Honors Program: Senior Projects (Public)
All populations display patterns in allele frequencies over time. Some alleles cease to exist, while some grow to become the norm. These frequencies can shift or stay constant based on the conditions the population lives in. If in Hardy-Weinberg equilibrium, the allele frequencies stay constant. Most populations, however, have bias from environmental factors, sexual preferences, other organisms, etc. We propose a stochastic Markov chain model to study allele progression across generations. In such a model, the allele frequencies in the next generation depend only on the frequencies in the current one.
We use this model to track a recessive allele …
Rewriting The Rules For Diagnostics: Implications Of Probability And Measure Theory For Sars-Cov-2 Testing, Paul Patrone, Anthony Kearsley
Rewriting The Rules For Diagnostics: Implications Of Probability And Measure Theory For Sars-Cov-2 Testing, Paul Patrone, Anthony Kearsley
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Computational Study Of Genotype-Phenotype Mutation Patterns, Kamaludin Dingle, Omar Tawfik, Ahmed Aldabagh
A Computational Study Of Genotype-Phenotype Mutation Patterns, Kamaludin Dingle, Omar Tawfik, Ahmed Aldabagh
Undergraduate Research Symposium
Understanding properties of genotype-phenotype maps is important for understanding biology and evolution. In this project we make a computational study of the statistical effects of genetic mutations, in particular computing the probabilities of each phenotype transitioning to any other phenotype. We also investigate the importance of the local phenotypic environment of a single genotype, and its role in determining mutation transition probabilities. We use HP protein folding, RNA structure, and a simplified GRN matrix model to study these questions.
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Electronic Theses and Dissertations
In this work, we seek to develop a variable screening and selection method for Bayesian mixture models with longitudinal data. To develop this method, we consider data from the Health and Retirement Survey (HRS) conducted by University of Michigan. Considering yearly out-of-pocket expenditures as the longitudinal response variable, we consider a Bayesian mixture model with $K$ components. The data consist of a large collection of demographic, financial, and health-related baseline characteristics, and we wish to find a subset of these that impact cluster membership. An initial mixture model without any cluster-level predictors is fit to the data through an MCMC …
Identification And Characterization Of De Novo Germline Tp53 Mutation Carriers In Families With Li-Fraumeni Syndrome, Carlos C. Vera Recio
Identification And Characterization Of De Novo Germline Tp53 Mutation Carriers In Families With Li-Fraumeni Syndrome, Carlos C. Vera Recio
Dissertations and Theses (Open Access)
Li-Fraumeni syndrome (LFS) is an inherited cancer syndrome caused by a deleterious mutation in TP53. An estimated 48% of LFS patients present due to a de novo mutation (DNM) in TP53. The knowledge of DNM status, DNM or familial mutation (FM), of an LFS patient requires genetic testing of both parents which is often inaccessible, making de novo LFS patients difficult to study. Famdenovo.TP53 is a Mendelian Risk prediction model used to predict DNM status of TP53 mutation carriers based on the cancer-family history and several input genetic parameters, including disease-gene penetrance. The good predictive performance of Famdenovo.TP53 was demonstrated …
Bayesian Techniques For Relating Genetic Polymorphisms To Diffusion Tensor Images Of Cocaine Users, Tmader Alballa
Bayesian Techniques For Relating Genetic Polymorphisms To Diffusion Tensor Images Of Cocaine Users, Tmader Alballa
Theses and Dissertations
Past investigations utilizing Diffusion Tensor Imaging (DTI) have demonstrated that cocaine use disorder (CUD) yields white matter changes. We proposed three Bayesian techniques in order to explore the relationship between Fractional Anisotropy (FA), genetic data, and years of cocaine use (YCU). CUD participants exhibit abnormality in different areas of the brain versus non-drug using controls, which is measured by DTI. This dissertation is motivated by a neuroimaging genetic study in cocaine dependence, which found that there were relationships between several genes such as GAD and 5-HT2R and CUD subjects.
In the first chapter, there is background on the …
Direct Questioning Of Sensitive Topics In Public Health Studies: A Simulation Study, Jessica K. Fox, Evrim Oral
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.
Predicting Diabetes Diagnoses, Sarah Netchert
Predicting Diabetes Diagnoses, Sarah Netchert
Student Research Poster Presentations 2020
This study explored the traits and health state of African Americans in central Virginia in order to determine what traits put people at a higher probability of being diagnosed with diabetes. We also want to know which traits will generate the highest probability a person will be diagnosed with diabetes. Traits that were included and used in this study were cholesterol, stabilized glucose, high density lipoprotein levels, age(years), gender, height(inches), weight(pounds), systolic blood pressure, diastolic blood pressure, waist size(inches), and hip size(inches). There were 403 individuals included in study since they were only ones screened for diabetes out of 1,046 …
Shrinkage Priors For Isotonic Probability Vectors And Binary Data Modeling, Philip S. Boonstra, Daniel R. Owen, Jian Kang
Shrinkage Priors For Isotonic Probability Vectors And Binary Data Modeling, Philip S. Boonstra, Daniel R. Owen, Jian Kang
The University of Michigan Department of Biostatistics Working Paper Series
This paper outlines a new class of shrinkage priors for Bayesian isotonic regression modeling a binary outcome against a predictor, where the probability of the outcome is assumed to be monotonically non-decreasing with the predictor. The predictor is categorized into a large number of groups, and the set of differences between outcome probabilities in consecutive categories is equipped with a multivariate prior having support over the set of simplexes. The Dirichlet distribution, which can be derived from a normalized cumulative sum of gamma-distributed random variables, is a natural choice of prior, but using mathematical and simulation-based arguments, we show that …
Statistical Inference For Networks Of High-Dimensional Point Processes, Xu Wang, Mladen Kolar, Ali Shojaie
Statistical Inference For Networks Of High-Dimensional Point Processes, Xu Wang, Mladen Kolar, Ali Shojaie
UW Biostatistics Working Paper Series
Fueled in part by recent applications in neuroscience, high-dimensional Hawkes process have become a popular tool for modeling the network of interactions among multivariate point process data. While evaluating the uncertainty of the network estimates is critical in scientific applications, existing methodological and theoretical work have only focused on estimation. To bridge this gap, this paper proposes a high-dimensional statistical inference procedure with theoretical guarantees for multivariate Hawkes process. Key to this inference procedure is a new concentration inequality on the first- and second-order statistics for integrated stochastic processes, which summarizes the entire history of the process. We apply this …
Characterizing The Permanence And Stationary Distribution For A Family Of Malaria Stochastic Models, Divine Wanduku
Characterizing The Permanence And Stationary Distribution For A Family Of Malaria Stochastic Models, Divine Wanduku
Biology and Medicine Through Mathematics Conference
No abstract provided.
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
COBRA Preprint Series
One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …
Analysis Of Ranked Gene Tree Probability Distributions Under The Coalescent Process For Detecting Anomaly Zones, Anastasiia Kim
Analysis Of Ranked Gene Tree Probability Distributions Under The Coalescent Process For Detecting Anomaly Zones, Anastasiia Kim
Shared Knowledge Conference
In phylogenetic studies, gene trees are used to reconstruct species tree. Under the multispecies coalescent model, gene trees topologies may differ from that of species trees. The incorrect gene tree topology (one that does not match the species tree) that is more probable than the correct one is termed anomalous gene tree (AGT). Species trees that can generate such AGTs are said to be in the anomaly zone (AZ). In this region, the method of choosing the most common gene tree as the estimate of the species tree will be inconsistent and will converge to an incorrect species tree when …
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Publications and Research
Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.
The Battle Against Malaria: A Teachable Moment, Randy K. Schwartz
The Battle Against Malaria: A Teachable Moment, Randy K. Schwartz
Journal of Humanistic Mathematics
Malaria has been humanity’s worst public health problem throughout recorded history. Mathematical methods are needed to understand which factors are relevant to the disease and to develop counter-measures against it. This article and the accompanying exercises provide examples of those methods for use in lower- or upper-level courses dealing with probability, statistics, or population modeling. These can be used to illustrate such concepts as correlation, causation, conditional probability, and independence. The article explains how the apparent link between sickle cell trait and resistance to malaria was first verified in Uganda using the chi-squared probability distribution. It goes on to explain …
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
UW Biostatistics Working Paper Series
We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …
Using Capture-Mark-Recapture Techniques To Estimate Detection Probabilities & Fidelity Of Expression For The Critically Endangered James Spinymussel (Pleurobema Collina)., Alaina C. Esposito
Using Capture-Mark-Recapture Techniques To Estimate Detection Probabilities & Fidelity Of Expression For The Critically Endangered James Spinymussel (Pleurobema Collina)., Alaina C. Esposito
Masters Theses, 2010-2019
The critically endangered James Spinymussel (Pleurobema collina) is a species of freshwater mussel endemic to Virginia’s James and Dan River basins. In the last 20 years, P. collina has experienced a substantial decline in numbers and currently occupies approximately 10% of its original habitat; however, little information is known about this species to assist in conservation. A 230-meter reach of transitional habitat in Swift Run was selected for repeat observations to estimate detection probabilities using a Capture-Mark-Recapture framework. In June 2014, visual scouting began to locate and tag P. collina (including other mussels in the community) with PIT …
Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly
Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly
CHIP Documents
This publication provides a contemporary treatment of the subject of meta-analysis in relation to social-personality psychology. Meta-analysis literally refers to the statistical pooling of the results of independent studies on a given subject, although in practice it refers as well to other steps of research synthesis, including defining the question under investigation, gathering all available research reports, coding of information about the studies and their effects, and interpretation/dissemination of results. Discussed as well are the hallmarks of high-quality meta-analyses.
Adaptive Randomization Designs, Jenna Colavincenzo
Adaptive Randomization Designs, Jenna Colavincenzo
Statistics
Adaptive design methodologies use prior information to develop a clinical trial design. The goal of an adaptive design is to maintain the integrity and validity of the study while giving the researcher flexibility in identifying the optimal treatment. An example of an adaptive design can be seen in a basic pharmaceutical trial. There are three phases of the overall trial to compare treatments and experimenters use the information from the previous phase to make changes to the subsequent phase before it begins.
Adaptive design methods have been in practice since the 1970s, but have become increasingly complex ever since. One …