Medicine and Health Sciences Commons^™

Bacteroides Fragilis In The Gut Microbiomes Of Alzheimer’S Disease Activates Microglia And Triggers Pathogenesis In Neuronal C/Ebpβ Transgenic Mice, Yiyuan Xia, Yifan Xiao, Zi-Hao Wang, Ashfaqul M. Alam, John P. Haran, Beth A. Mccormick, Xiji Shu, Xiaochuan Wang, Keqiang Ye

Markey Cancer Center Faculty Publications

Gut dysbiosis contributes to Alzheimer’s disease (AD) pathogenesis, and Bacteroides strains are selectively elevated in AD gut microbiota. However, it remains unknown which Bacteroides species and how their metabolites trigger AD pathologies. Here we show that Bacteroides fragilis and their metabolites 12-hydroxy-heptadecatrienoic acid (12-HHTrE) and Prostaglandin E2 (PGE2) activate microglia and induce AD pathogenesis in neuronal C/EBPβ transgenic mice. Recolonization of antibiotics cocktail-pretreated Thy1-C/EBPβ transgenic mice with AD patient fecal samples elicits AD pathologies, associated with C/EBPβ/Asparaginyl endopeptidase (AEP) pathway upregulation, microglia activation, and cognitive disorders compared to mice receiving healthy donors’ fecal microbiota transplantation (FMT). Microbial 16S rRNA sequencing …

Syne1 Mutation Is Associated With Increased Tumor Mutation Burden And Immune Cell Infiltration In Ovarian Cancer, Laura M. Harbin, Nan Lin, Frederick R. Ueland, Jill M. Kolesar

Markey Cancer Center Faculty Publications

SYNE1, a nuclear envelope protein critical for cellular structure and signaling, is downregulated in numerous malignancies. SYNE1 alterations are found in 10% of gynecologic malignancies and 5% of epithelial ovarian cancers. Previous studies demonstrated an association between SYNE1 mutation, increased tumor mutation burden (TMB), and immunotherapy response. This study evaluates the SYNE1 mutation frequency, association with TMB, and downstream effects of SYNE1 mutation in ovarian cancer. Genetic information, including whole-exome sequencing, RNA analysis, and somatic tumor testing, was obtained for consenting ovarian cancer patients at an academic medical center. Mutation frequencies were compared between the institutional cohort and The Cancer …

Unleashing The Potential Of 1,3-Diketone Analogues As Selective Lh2 Inhibitors, Juhoon Lee, Hou-Fu Guo, Shike Wang, Yazdan Maghsoud, Erik Antonio Vázquez-Montelongo, Zhifeng Jing, Rae M. Sammons, Eun Jeong Cho, Pengyu Ren, G. Andrés Cisneros, Jonathan M. Kurie, Kevin N. Dalby

Markey Cancer Center Faculty Publications

Lysyl hydroxylase 2 (LH2) catalyzes the formation of highly stable hydroxylysine aldehyde-derived collagen cross-links (HLCCs), thus promoting lung cancer metastasis through its capacity to modulate specific types of collagen cross-links within the tumor stroma. Using 1 and 2 from our previous high-throughput screening (HTS) as lead probes, we prepared a series of 1,3-diketone analogues, 1−18, and identified 12 and 13 that inhibit LH2 with IC50’s of approximately 300 and 500 nM, respectively. Compounds 12 and 13 demonstrate selectivity for LH2 over LH1 and LH3. Quantum mechanics/molecular mechanics (QM/MM) modeling indicates that the selectivity of 12 and 13 may stem from …

Antiviral Susceptibility Of Clade 2.3.4.4b Highly Pathogenic Avian Influenza A(H5n1) Viruses Isolated From Birds And Mammals In The United States, 2022, Ha T. Nguyen, Anton Chesnokov, Juan De La Cruz, Philippe Noriel Q. Pascua, Vasiliy P. Mishin, Yunho Jang, Joyce Jones, Han Di, Andrei A. Ivashchenko, Mary Lea Killian, Mia K. Torchetti, Kristina Lantz, David E. Wentworth, Charles T. Davis, Alexandre V. Ivachtchenko, Larisa V. Gubareva

United States Department of Agriculture Wildlife Services: Staff Publications

Clade 2.3.4.4b highly pathogenic avian influenza (HPAI) A(H5N1) viruses that are responsible for devastating outbreaks in birds and mammals pose a potential threat to public health. Here, we evaluated their susceptibility to influenza antivirals. Of 1,015 sequences of HPAI A(H5N1) viruses collected in the United States during 2022, eight viruses (∼0.8%) had a molecular marker of drug resistance to an FDA-approved antiviral: three adamantane-resistant (M2-V27A), four oseltamivir-resistant (NA-H275Y), and one baloxavir-resistant (PA-I38T). Additionally, 31 viruses contained mutations that may reduce susceptibility to inhibitors of neuraminidase (NA) (n = 20) or cap-dependent endonuclease (CEN) (n = 11). A panel of 22 …

Significant Improvement Of Fidelity For Encoded Quantum Bell Pairs At Long And Short-Distance Communication Along With Generalized Circuit, Syed Emad Uddin Shubha, Md Saifur Rahman, M R C Mahdy

Faculty, Staff and Student Publications

Quantum entanglement is a unique criterion of the quantum realm and an essential tool to secure quantum communication. Ensuring high-fidelity entanglement has always been a challenging task owing to interaction with the hostile channel environment created due to quantum noise and decoherence. Though several methods have been proposed, correcting almost all arbitrary errors is still a gigantic task. As one of the main contributions of this work, a new model for 'large distance communication' has been proposed, which may correct all bit flip errors or other errors quite extensively if proper encoding and subspace measurements are used. To achieve this …

Low Pitch Significantly Reduces Helical Artifacts In Abdominal Ct, Moiz Ahmad, Peng Sun, Christine B Peterson, Marcus R Anderson, Xinming Liu, Ajaykumar C Morani, Corey T Jensen

Faculty, Staff and Student Publications

Purpose: High helical pitch scanning minimizes scan times in CT imaging, and thus also minimizes motion artifact and mis-synchronization with contrast bolus. However, high pitch produces helical artifacts that may adversely affect diagnostic image quality. This study aims to determine the severity and incidence of helical artifacts in abdominal CT imaging and their relation to the helical pitch scan parameter.

Methods: To obtain a dataset with varying pitch values, we used CT exam data both internal and external to our center. A cohort of 59 consecutive adult patients receiving an abdomen CT examination at our center with an accompanying prior …

Computational And Experimental Investigation Of Elemental Sulfur And Polysulfide, Jyoti Sharma

Dissertations

Petroleum processing results in the generation of significant quantities of elemental sulfur (S₈), leading to a surplus of sulfur worldwide. Despite its abundance and low cost, the use of sulfur in value-added organic compound synthesis is limited due to its unpredictable and misunderstood reactivity. This dissertation aims to address this issue by tackling it from two angles. Firstly, by utilizing Density Functional Theory (DFT) calculations, the reactivity of sulfur in the presence of nucleophiles is studied. This facilitates the identification of organic polysulfide intermediates that can be generated under different conditions, as well as the corresponding reactivity for …

Healthy Lifestyle Behaviors And Sociodemographic Characteristics Among Medical Students In Indonesia During The New Normal Era: A Cross-Sectional Study, Sharren Shera Vionnetta, Tommy Nugroho Tanumihardja, Kevin Kristian

Kesmas

This study aimed to identify medical students’ healthy lifestyle behaviors during the new normal era and to determine its relationship with sociodemographic factors, bearing in mind that, as future physicians and health role models, medical students play an important role in adopting and promoting healthy lifestyle behaviors to reduce the risk of future health problems as well as optimize communities’ health status. This cross-sectional study was conducted at the School of Medicine and Health Sciences of Universitas Katolik Indonesia Atma Jaya, with 111 medical students selected through stratified random sampling. Data were collected using sociodemographic characteristics (sex, residence, year of …

Self-Reported Consumption Of Bottled Water V. Tap Water In Appalachian And Non-Appalachian Kentucky, Jason W. Marion

Journal of Appalachian Health

Introduction: Quantitative studies on drinking water perceptions in Appalachia are limited. High-profile water infrastructure failures in the U.S. and Eastern Kentucky, coupled with human-made and natural disasters in the Appalachian Region, have likely impacted opinions regarding tap water.

Purpose: To use existing unexplored data to describe baseline tap water v. bottled water consumption in Kentucky.

Methods: Telephone-based cross-sectional data were obtained from the 2013 Kentucky Health Issues Poll (KHIP) directed by the Foundation for a Healthy Kentucky. Among many items in KHIP, self-reported consumption of bottled water over tap water, reasons for bottled water use, and demographic data were obtained. …

Prediction Of Factors For Patients With Hypertension And Dyslipidemia Using Multilayer Feedforward Neural Networks And Ordered Logistic Regression Analysis: A Robust Hybrid Methodology, Wan Muhamad Amir W Ahmad, Mohamad Nasarudin Bin Adnan, Norhayati Yusop, Hazik Bin Shahzad, Farah Muna Mohamad Ghazali, Nor Azlida Aleng, Nor Farid Mohd Noor

Makara Journal of Health Research

Background: Hypertension is characterized by abnormally high arterial blood pressure and is a public health problem with a high prevalence of 20%–30% worldwide. This research combined multiple logistic regression (MLR) and multilayer feedforward neural networks to construct and validate a model for evaluating the factors linked with hypertension in patients with dyslipidemia.

Methods: A total of 1000 data entries from Hospital Universiti Sains Malaysia and advanced computational statistical modeling methodologies were used to evaluate seven traits associated with hypertension. R-Studio software was utilized. Each sample's statistics were calculated using a hybrid model that included bootstrapping.

Results: Variable …

Artificial Intelligence In Cardiology: An Australian Perspective, Biyanka Jaltotage, Abdul R. Ihdayhid, Nick S. R. Lan, Faraz Pathan, Sanjay Patel, Clare Arnott, Gemma Figtree, Leonard Kritharides, Syed M. S. Islam, Clara K. Chow, James M. Rankin, Stephen J. Nicholls, Girish Dwivedi

Research outputs 2022 to 2026

Significant advances have been made in artificial intelligence technology in recent years. Many health care applications have been investigated to assist clinicians and the technology is close to being integrated into routine clinical practice. The high prevalence of cardiac disease in Australia places overwhelming demands on the existing health care system, challenging its capacity to provide quality patient care. Artificial intelligence has emerged as a promising solution. This discussion paper provides an Australian perspective on the current state of artificial intelligence in cardiology, including the benefits and challenges of implementation. This paper highlights some current artificial intelligence applications in cardiology, …

Crabr-Net: A Contextual Relational Attention-Based Recognition Network For Remote Sensing Scene Objective, Ningbo Guo, Mingyong Jiang, Lijing Gao, Yizhuo Tang, Jinwei Han, Xiangning Chen

Faculty, Staff and Student Publications

Remote sensing scene objective recognition (RSSOR) plays a serious application value in both military and civilian fields. Convolutional neural networks (CNNs) have greatly enhanced the improvement of intelligent objective recognition technology for remote sensing scenes, but most of the methods using CNN for high-resolution RSSOR either use only the feature map of the last layer or directly fuse the feature maps from various layers in the "summation" way, which not only ignores the favorable relationship information between adjacent layers but also leads to redundancy and loss of feature map, which hinders the improvement of recognition accuracy. In this study, a …

Sctiger: A Deep-Learning Method For Inferring Gene Regulatory Networks From Case Versus Control Scrna-Seq Datasets., Madison Dautle, Shaoqiang Zhang, Yong Chen

College of Science & Mathematics Departmental Research

Inferring gene regulatory networks (GRNs) from single-cell RNA-seq (scRNA-seq) data is an important computational question to find regulatory mechanisms involved in fundamental cellular processes. Although many computational methods have been designed to predict GRNs from scRNA-seq data, they usually have high false positive rates and none infer GRNs by directly using the paired datasets of case-versus-control experiments. Here we present a novel deep-learning-based method, named scTIGER, for GRN detection by using the co-differential relationships of gene expression profiles in paired scRNA-seq datasets. scTIGER employs cell-type-based pseudotiming, an attention-based convolutional neural network method and permutation-based significance testing for inferring GRNs among …

Forecasting Stock Indices With The Covid-19 Infection Rate As An Exogenous Variable, Mohammad Saha A. Patwary

School of Computing and Informatics

Forecasting stock market indices is challenging because stock prices are usually nonlinear and non- stationary. COVID-19 has had a significant impact on stock market volatility, which makes forecasting more challenging. Since the number of confirmed cases significantly impacted the stock price index; hence, it has been considered a covariate in this analysis. The primary focus of this study is to address the challenge of forecasting volatile stock indices during Covid-19 by employing time series analysis. In particular, the goal is to find the best method to predict future stock price indices in relation to the number of COVID-19 infection rates. …

Table Of Contents

Journal of the South Carolina Academy of Science

No abstract provided.

Machine Learning-Based Classification Of Chronic Traumatic Brain Injury Using Hybrid Diffusion Imaging, Jennifer Muller, Ruixuan Wang, Devon Middleton, Mahdi Alizadeh, Kichang Kang, Ryan Hryczyk, George Zabrecky, Chloe Hriso, Emily Navarreto, Nancy Wintering, Anthony J. Bazzan, Chengyuan Wu, Daniel A. Monti, Xun Jiao, Qianhong Wu, Andrew B. Newberg, Feroze Mohamed

Marcus Institute of Integrative Health Faculty Papers

BACKGROUND AND PURPOSE: Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging.

MATERIALS AND METHODS: A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging …

One Font Doesn’T Fit All: The Influence Of Digital Text Personalization On Comprehension In Child And Adolescent Readers, Shannon M. Sheppard, Susanne L. Nobles, Anton Palma, Sophie Kajfez, Marjorie Jordan, Kathy Crowley, Sofie Beier

Communication Sciences and Disorders Faculty Articles and Research

Reading comprehension is an essential skill. It is unclear whether and to what degree typography and font personalization may impact reading comprehension in younger readers. With advancements in technology, it is now feasible to personalize digital reading formats in general technology tools, but this feature is not yet available for many educational tools. The current study aimed to investigate the effect of character width and inter-letter spacing on reading speed and comprehension. We enrolled 94 children (kindergarten–8th grade) and compared performance with six font variations on a word-level semantic decision task (Experiment 1) and a passage-level comprehension task (Experiment 2). …

Characteristics And Source-Specific Health Risks Of Ambient Pm2.5-Bound Pahs In An Urban City Of Northern Taiwan, Yu-Chieh Ting, Chun-Hung Ku, Yu-Xuan Zou, Kai-Hsien Chi, Jhy-Charm Soo, Chin-Yu Hsu, Yu-Cheng Chen

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Polycyclic aromatic hydrocarbons (PAHs) with highly toxic compounds mainly exist in small-sized particles and can induce considerable human health risks. Studies on PM2.5-bound PAHs and their source-specific human health risks still remain scarce. Daily PM2.5 samples (n = 119) were collected every three days from 2016 to 2017 in Taipei city, Taiwan. Fifteen PAHs in PM2.5 were analyzed via gas chromatography tandem mass spectrometry (GC/MS-MS). We utilized a positive matrix factorization (PMF) model, diagnostic ratios, and potential source contribution function (PSCF) to identify the origins of PM2.5-bound PAHs. The annual concentration of total PAHs (TPAH) was 0.79 ± 0.67 ng …

Scale Model Experiments Of Toxic Gas Production From The Combustion Of Polymers When Applied With Different Droplet Sizes Of Water Mist, Nicharee Thinnakornsutubutr, Masayuki Mizuno, Kazunori Kuwana

Progress in Scale Modeling, an International Journal

This research experimentally investigated the combustion of polymeric materials with water mist application in an enclosure, with an emphasis on the production of toxic gases. Two different diameters, ~100 and ~260 μm, were tested. The experimental conditions were determined based on Froude similarity laws for low drop Reynolds number conditions. Droplets and polymers’ physical and chemical properties influence the burning/extinguishing behavior and toxic-gas evolution. In general, larger droplets can extinguish a fire in a shorter time, and toxic gas concentrations in a test chamber decreased more rapidly. However, the large droplets tended to cause the flame expansion phenomenon for thermoplastics …

Stability Analyses On The Effect Of Vaccination And Contact Tracing In Monkeypox Virus Transmission, Solomon Eshun, Richmond Essieku, James Ladzekpo

School of Mathematical & Statistical Sciences Faculty Publications

Monkeypox is a significant health concern due to its potential for morbidity and occasional mortality. Vaccination and effective contact tracing play pivotal roles in controlling infectious diseases, including monkeypox. This study aims to contribute to our understanding of monkeypox dynamics by developing a comprehensive mathematical model that incorporates key factors such as vaccination, quarantining, and contact tracing. Through rigorous sensitivity analysis, we explore the impact of varying vaccination coverage and contact tracing on the disease’s dynamics. In particular, we investigate the dynamics of the disease in relation to variable vaccination coverage and contact tracing. Our findings highlight the critical role …

Additive Effects Of Cyclic Peptide [R4w4] When Added Alongside Azithromycin And Rifampicin Against Mycobacterium Avium Infection, Melissa Kelley, Kayvan Sasaninia, Arbi Abnousian, Ali Badaoui, James Owens, Abrianna Beever, Nala Kachour, Rakesh Kumar Tiwari, Vishwanath Venketaraman

Pharmacy Faculty Articles and Research

Mycobacterium avium (M. avium), a type of nontuberculous mycobacteria (NTM), poses a risk for pulmonary infections and disseminated infections in immunocompromised individuals. Conventional treatment consists of a 12-month regimen of the first-line antibiotics rifampicin and azithromycin. However, the treatment duration and low antibiotic tolerability present challenges in the treatment of M. avium infection. Furthermore, the emergence of multidrug-resistant mycobacterium strains prompts a need for novel treatments against M. avium infection. This study aims to test the efficacy of a novel antimicrobial peptide, cyclic [R4W4], alongside the first-line antibiotics azithromycin and rifampicin in reducing M. avium survival. Colony-forming unit (CFU) …

Federated Generalized Linear Mixed Models For Collaborative Genome-Wide Association Studies, Wentao Li, Han Chen, Xiaoqian Jiang, Arif Harmanci

Faculty, Staff and Student Publications

Federated association testing is a powerful approach to conduct large-scale association studies where sites share intermediate statistics through a central server. There are, however, several standing challenges. Confounding factors like population stratification should be carefully modeled across sites. In addition, it is crucial to consider disease etiology using flexible models to prevent biases. Privacy protections for participants pose another significant challenge. Here, we propose distributed Mixed Effects Genome-wide Association study (

Systematic Design And Data-Driven Evaluation Of Social Determinants Of Health Ontology (Sdoho), Yifang Dang, Fang Li, Xinyue Hu, Vipina K Keloth, Meng Zhang, Sunyang Fu, Muhammad F Amith, J Wilfred Fan, Jingcheng Du, Evan Yu, Hongfang Liu, Xiaoqian Jiang, Hua Xu, Cui Tao

Faculty, Staff and Student Publications

Objective: Social determinants of health (SDoH) play critical roles in health outcomes and well-being. Understanding the interplay of SDoH and health outcomes is critical to reducing healthcare inequalities and transforming a "sick care" system into a "health-promoting" system. To address the SDOH terminology gap and better embed relevant elements in advanced biomedical informatics, we propose an SDoH ontology (SDoHO), which represents fundamental SDoH factors and their relationships in a standardized and measurable way.

Material and methods: Drawing on the content of existing ontologies relevant to certain aspects of SDoH, we used a top-down approach to formally model classes, relationships, and …

A Lifecycle Framework Illustrates Eight Stages Necessary For Realizing The Benefits Of Patient-Centered Clinical Decision Support, Dean F Sittig, Aziz Boxwala, Adam Wright, Courtney Zott, Priyanka Desai, Rina Dhopeshwarkar, James Swiger, Edwin A Lomotan, Angela Dobes, Prashila Dullabh

Faculty, Staff and Student Publications

The design, development, implementation, use, and evaluation of high-quality, patient-centered clinical decision support (PC CDS) is necessary if we are to achieve the quintuple aim in healthcare. We developed a PC CDS lifecycle framework to promote a common understanding and language for communication among researchers, patients, clinicians, and policymakers. The framework puts the patient, and/or their caregiver at the center and illustrates how they are involved in all the following stages: Computable Clinical Knowledge, Patient-specific Inference, Information Delivery, Clinical Decision, Patient Behaviors, Health Outcomes, Aggregate Data, and patient-centered outcomes research (PCOR) Evidence. Using this idealized framework reminds key stakeholders that …

Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte

Faculty Publications

The adoption of whole slide image (WSI) scanners in clinical practice was accelerated by US Food and Drug Administration approval in 2017, which allowed primary pathologic diagnoses to be made on scanned images. Images in the digital domain allow the application of pathology artificial intelligence (AI), including clinical decision support with algorithms performing specific diagnoses.1,2 These algorithms, if trained properly, could go beyond the ability of human observation to detect and quantify features that are not recognizable by human perception.1,3,4

Developing Electronic Clinical Quality Measures To Assess The Cancer Diagnostic Process, Daniel R Murphy, Andrew J Zimolzak, Divvy K Upadhyay, Li Wei, Preeti Jolly, Alexis Offner, Dean F Sittig, Saritha Korukonda, Riyaa Murugaesh Rekha, Hardeep Singh

Faculty, Staff and Student Publications

OBJECTIVE: Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance.

MATERIALS AND METHODS: We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of …

Sickle Cell Disease Treatment With Arginine Therapy (Start): Study Protocol For A Phase 3 Randomized Controlled Trial., Chris A Rees, David C. Brousseau, Daniel M Cohen, Anthony Villella, Carlton Dampier, Kathleen Brown, Andrew Campbell, Corrie E Chumpitazi, Gladstone Airewele, Todd Chang, Christopher Denton, Angela Ellison, Alexis Thompson, Fahd Ahmad, Nitya Bakshi, Keli D Coleman, Sara Leibovich, Deborah Leake, Dunia Hatabah, Hagar Wilkinson, Michelle Robinson, T Charles Casper, Elliott Vichinsky, Claudia R Morris

Department of Pediatrics Faculty Papers

BACKGROUND: Despite substantial illness burden and healthcare utilization conferred by pain from vaso-occlusive episodes (VOE) in children with sickle cell disease (SCD), disease-modifying therapies to effectively treat SCD-VOE are lacking. The aim of the Sickle Cell Disease Treatment with Arginine Therapy (STArT) Trial is to provide definitive evidence regarding the efficacy of intravenous arginine as a treatment for acute SCD-VOE among children, adolescents, and young adults.

METHODS: STArT is a double-blind, placebo-controlled, randomized, phase 3, multicenter trial of intravenous arginine therapy in 360 children, adolescents, and young adults who present with SCD-VOE. The STArT Trial is being conducted at 10 …

The Devil You Know And The Devil You Don’T: Current Status And Challenges Of Bovine Tuberculosis Eradication In The United States, Daniel J. O'Brien, Tyler C. Thacker, Liliana C.M. Salvador, Anthony G. Duffiney, Suelee Robbe‑Austerman, Mark S. Camacho, Jason E. Lombard, Mitchell V. Palmer

United States Department of Agriculture Wildlife Services: Staff Publications

Having entered into its second century, the eradication program for bovine tuberculosis (bTB, caused by Mycobacterium bovis) in the United States of America occupies a position both enviable and daunting. Excepting four counties in Michigan comprising only 6109 km2 (0.06% of US land area) classified as Modified Accredited, as of April 2022 the entire country was considered Accredited Free of bTB by the US Department of Agriculture for cattle and bison. On the surface, the now well-described circumstances of endemic bTB in Michigan, where white-tailed deer (Odocoileus virginianus) serve as a free-ranging wildlife maintenance host, may appear to be …

Atrial Fibrillation Management In Hispanic Adults, Tania Borja

Dissertations

Background: Research has found atrial fibrillation (AF) to be the primary or a contributing cause of death on 183,321 death certificates, and an underlying cause of death for 26,535 Americans in 2019. Findings indicate an increased AF diagnosis in White people compared to racial and ethnic minorities, contrasting widespread findings of increased prevalence of cardiovascular disease and ischemic strokes in minorities. Significant disparities—by race and socioeconomic status in disease distribution and access to testing and lifesaving treatments—have been documented, specifically associated with social determinants of health (SDOH); i.e., the conditions in which people are born, grow, live, work, and age. …

Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney

Theses and Dissertations

Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …