Physical Sciences and Mathematics Commons^™

Big Data Applications And Challenges In Giscience (Case Studies: Natural Disaster And Public Health Crisis Management), Amir Masoud Forati

Theses and Dissertations

This dissertation examines the application and significance of user-generated big data in Geographic Information Science (GIScience), with a focus on managing natural disasters and public health crises. It explores the role of social media data in understanding human-environment interactions and in informing disaster management and public health strategies. A scalable computational framework will be developed to model extensive unstructured geotagged data from social media, facilitating systematic spatiotemporal data analysis.The research investigates how individuals and communities respond to high-impact events like natural disasters and public health emergencies, employing both qualitative and quantitative methods. In particular, it assesses the impact of socio-economic-demographic …

Pipeline For Calculating Calories For Print Recipes With Minimal User Intervention, Karl W. Holten

Theses and Dissertations

The thesis will provide a pipeline to estimate calorie counts from print recipes. The pipeline takes scanned recipes from cookbooks and uses Optical Character Recognition (OCR) to convert the scanned images of recipes to text. Several OCR tools were tested for their accuracy on fractions using a sample of the data, and the most accurate tool is used on the data. Next, a specially trained named entity recognition model is used to identify ingredients, quantities and units. These ingredients are used to search a database of values from the FDA to compute a calorie count for the recipe. The thesis …

Exploring The Spatial Distribution Of Air Pollutants And Covid-19 Death Rate: A Case Study For Los Angeles County, California, Akhil Mandalapu, Junfeng Jiao, Amin Azimian

International Journal of Geospatial and Environmental Research

Objective

Since March 2020, COVID-19 has rapidly spread across the world with over 240 million cases and over 5 million deaths as of November 2021. It has been unclear what role air pollutants may play in exacerbating respiratory illnesses such as COVID-19 due to their interaction with the respiratory system. The association with air pollutants and COVID-19 severity has been explored at the regional and metropolitan area, however it is unclear if such an association is consistent at the neighborhood level.

Methods

Weekly death rates from COVID-19 from March 2020 to November 2021 were compared using one-sided unpaired t-tests across …

Geospatial Clustering And Hot Spot Detection Of Covid-19 Incidence In 2020: A Global Analysis, Munazza Fatima, Sana Arshad, Ibtisam Butt, Saba Arshad

International Journal of Geospatial and Environmental Research

Emergence and spread of Covid-19 initiated diversified researches based on spatial analysis in visualization, exploration, and modelling of this infection. This short communication is an attempt to comprehend the geographic distribution and spatial clustering of Covid-19 in year 2020. Main objective is to spatially analyze Covid-19 incidence rates, identification of hotspots and clusters outliers at global level. Monthly data of reported cases were taken from World Health Organization dashboard and situation reports. Incidence rate was calculated for each country for each month. Spatial autocorrelation techniques of Global Moran are I and Anselian Local Moran’s I were used to examine the …

Two Essays On Leveraging Analytics To Improve Healthcare, Deepika Gopukumar

Theses and Dissertations

The healthcare cost has continued to increase over the past few years despite various policies, efforts, and initiatives taken by the government. It is still projected to grow over the next few years by the Centers for Medicare and Medicaid Services (CMS). Readmissions have been a major contributor to the increase in costs and have always been a contributing factor. To get a perspective, considering the fact that at least 9% of individuals who had COVID-19 were likely to get readmitted shortly, according to a study by the Centers for Disease Control and Prevention (CDC) COVID-19 response team, along with …

Machine-Learning-Based Prediction Of Sepsis Events From Vertical Clinical Trial Data: A Naïve Approach, Tyler Michael Gaddis

Theses and Dissertations

Sepsis is a potentially life-threatening condition characterized by a dysregulated, disproportionate immune response to infection by which the afflicted body attacks its own tissues, sometimes to the point of organ failure, and in the worst cases, death. According to the Centers for Disease Control and Prevention (CDC) Sepsis is reported to kill upwards of 270,000 Americans annually, though this figure may be greater given certain ambiguities in the current accepted diagnostic framework of the disease.

This study attempted to first establish an understanding of past definitions of sepsis, and to then recommend use of machine learning as integral in an …

Infant Mortality In The United States: Socioeconomic Factors Predicting Infant Survival In Late Neo-Natal And Post Neo-Natal Infants From Birth Certificate Data, Mark Brunk-Grady

Theses and Dissertations

According to the Centers for Disease Control and Prevention, the infant mortality rate in the United States in 2018 was 5.6 deaths per 1000 live births. Infant mortality is defined as a child being born alive but dying before their first birthday. This study aimed to determine if adding socioeconomic factors to traditional predictive survival models improved the predictive power in terms of survival for late and post neonatal infants. Secondly, this study looked to develop a risk score to and predict which mothers would be classified as “High” or “Low” risk for infant death.

Data were analyzed from a …

Stability Analysis For The Equilibria Of A Monkeypox Model, Rachel Elizabeth Tewinkel

Theses and Dissertations

Monkeypox virus was first identified in 1958 and has since been an ongoing problem in Central and Western Africa. Although the smallpox vaccine provides partial immunity against monkeypox, the number of cases has greatly increased since the eradication of smallpox made its vaccination unnecessary. Although studied by epidemiologists, monkeypox has not been thoroughly studied by mathematicians to the extent of other serious diseases. Currently, to our knowledge, only three mathematical models of monkeypox have been proposed and studied. We present the first of these models, which is related to the second, and discuss the global and local asymptotic stability of …

Network Analysis Of Scientific Collaboration And Co-Authorship Of The Trifecta Of Malaria, Tuberculosis And Hiv/Aids In Benin., Gbedegnon Roseric Azondekon

Theses and Dissertations

Despite the international mobilization and increase in research funding, Malaria, Tuberculosis and HIV/AIDS are three infectious diseases that have claimed more lives in sub Saharan Africa than any other place in the World. Consortia, research network and research centers both in Africa and around the world team up in a multidisciplinary and transdisciplinary approach to boost efforts to curb these diseases. Despite the progress in research, very little is known about the dynamics of research collaboration in the fight of these Infectious Diseases in Africa resulting in a lack of information on the relationship between African research collaborators. This dissertation …

Point Of Use Biosand Filters Of The Rural Dominican Republic, Kurtis Quamme

Theses and Dissertations

The point of use biosand filter (BSF) is used globally as a drinking water treatment solution. In this research, point of use BSFs were inoculated with active biosand from the Linnwood Drinking Water Treatment plant slow sand filter beds (Milwaukee, Wisconsin) and with sands collected from point of use filters operating in the Dominican Republic. These filters were maintained with varying source waters (surface water, groundwater, or tap water to simulate chlorination encountered in the field). The microbial community of filters with varied influents and biosand inoculum were analyzed quantitatively by sequencing and qPCR. Filter efficacy and microbial community were …

Three Essays On Enhancing Clinical Trial Subject Recruitment Using Natural Language Processing And Text Mining, Euisung Jung

Theses and Dissertations

Patient recruitment and enrollment are critical factors for a successful clinical trial; however, recruitment tends to be the most common problem in most clinical trials. The success of a clinical trial depends on efficiently recruiting suitable patients to conduct the trial. Every clinical trial research has a protocol, which describes what will be done in the study and how it will be conducted. Also, the protocol ensures the safety of the trial subjects and the integrity of the data collected. The eligibility criteria section of clinical trial protocols is important because it specifies the necessary conditions that participants have to …

Using Omaha System Documentation To Understand Physical Activity Among Rural Women, Jeanette Melissa Olsen

Theses and Dissertations

Rural women are more inactive and have different barriers to physical activity than those who live in more urban settings, yet few studies have specifically examined physical activity and associated factors in this population. Clinical data documented with standardized terminology by nurses caring for rural women may provide an opportunity to generate evidence that informs and improves nursing care. However, the knowledge to be gained and utility of nurses' clinical documentation in regard to physical activity have not been explored. Accordingly, the purpose of this study was to increase understanding of physical activity and associated factors among rural women by …

Citefinder: A System To Find And Rank Medical Citations, Seyed Soheil Moosavinasab

Theses and Dissertations

This thesis presents CiteFinder, a system to find relevant citations for clinicians' written content. Inclusion of citations for clinical information content makes the content more reliable through the provision of scientific articles as references, and enables clinicians to easily update their written content using new information. The proposed approach splits the content into sentences, identifies the sentences that need to be supported with citations by applying classification algorithms, and uses information retrieval and ranking techniques to extract and rank relevant citations from MEDLINE for any given sentence. Additionally, this system extracts snippets from the retrieved articles. We assessed our approach …

Transcending Microbial Source Tracking Techniques Across Geographic Borders: An Examination Of Human And Animal Microbiomes And The Integration Of Molecular Approaches In Pathogen Surveillance In Brazil And The United States, Amber Mae Koskey

Theses and Dissertations

Waterborne illnesses, attributed to the ingestion or contact with contaminated water, present a significant global health concern. Surface water sources can be impacted by wide array of pollution inputs, but fecal pollution generates the most significant and acute threat to human health. Therefore, the detection of fecal bacteria in surface water sources remains an important public health objective. Current surface water monitoring employs the use of fecal indicator bacteria (FIB) including E. coli and enterococci as proxies for pathogenic organisms carried in fecal pollution. These traditional indicators, detected by culture-based microbiological methods, do not discriminate fecal sources from another. New …

Complexity And Uncertainty In Human And Ecological Risk Assessment, Matthew Jordan Dellinger

Theses and Dissertations

Multiple interacting stressors in the environment present increasingly complex risks to human health. Too often, however, the data required for traditional risk assessment are either lacking or unavailable at the necessary spatial or temporal scale. In addition, assessment practices and management policies need to move away from single factor approaches in order to accommodate the reality of complex chemical mixtures and environmental stressors. Recent literature suggests that a paradigm shift is under way. This points to a need for the development of new techniques both for rapid data collection and flexible risk assessment strategies that can adapt to make use …

An Efficient Methodology For Learning Bayesian Networks, Emmanuel Owusu Asante-Asamani

Theses and Dissertations

Statistics from the National Cancer Institute indicate that 1 in 8 women will develop Breast cancer in their lifetime. Researchers have developed numerous statistical models to predict breast cancer risk however physicians are hesitant to use these models because of disparities in the predictions they produce. In an effort to reduce these disparities, we use Bayesian networks to capture the joint distribution of risk factors, and simulate artificial patient populations (clinical avatars) for interrogating the existing risk prediction models. The challenge in this effort has been to produce a Bayesian network whose dependencies agree with literature and are good estimates …