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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Bivariate Markov Chain Model Of Irritable Bowel Syndrome (Ibs) Subtypes And Abdominal Pain, Ricardo Reyna Jr. Dec 2020

Bivariate Markov Chain Model Of Irritable Bowel Syndrome (Ibs) Subtypes And Abdominal Pain, Ricardo Reyna Jr.

Theses and Dissertations

Researchers use stochastic models like continuous-time Markov chains (CTMC) to model progression of morbidities of public health impact, like HIV and Hepatitis C. Most of the research in that area is done for a single disease. In this research, we use a bivariate continuous-time Markov chain (CTMC) to model progression of co-morbidities. In particular, we use a bivariate CTMC to model the joint progression of Irritable Bowel Syndrome (IBS) and abdominal pain. Symptoms of IBS are known to change throughout the duration of the disorder. Hence, patients are normally asked to make a journal of the stool type, symptoms, and …


Machine-Learning-Based Prediction Of Sepsis Events From Vertical Clinical Trial Data: A Naïve Approach, Tyler Michael Gaddis Aug 2020

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 …


Prediction Of Drug-Drug Interaction Potential Using Machine Learning Approaches, Joseph Scavetta May 2020

Prediction Of Drug-Drug Interaction Potential Using Machine Learning Approaches, Joseph Scavetta

Theses and Dissertations

Drug discovery is a long, expensive, and complex, yet crucial process for the benefit of society. Selecting potential drug candidates requires an understanding of how well a compound will perform at its task, and more importantly, how safe the compound will act in patients. A key safety insight is understanding a molecule's potential for drug-drug interactions. The metabolism of many drugs is mediated by members of the cytochrome P450 superfamily, notably, the CYP3A4 enzyme. Inhibition of these enzymes can alter the bioavailability of other drugs, potentially increasing their levels to toxic amounts. Four models were developed to predict CYP3A4 inhibition: …


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 May 2020

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 …


Mathematical Modeling Of Nonlinear Dynamics Of Blood Hormones On The Regulatory System, Gabriela Urbina May 2020

Mathematical Modeling Of Nonlinear Dynamics Of Blood Hormones On The Regulatory System, Gabriela Urbina

Theses and Dissertations

We study a mathematical modeling of nonlinear dynamics of blood hormones, which includes glucose and insulin. On Chapter I, II, III and IV, we introduce this work, analyze an effect of the secreted insulin by the pancreatic beta cells and glucagon hormones and state concluding remarks, respectively. This model considers the time evolution of nonlinear dynamics of the equations for glucose, glucagon and insulin concentrations plus insulin and glucagon actions and the secreted insulin as a result of elevation of glucose in the blood plasma. Using both analytical and numerical procedures, we determine such quantities using different parameters for different …


Electronic Image Detectability Under Varying Illumination Conditions, Jeremy J. Miller Mar 2020

Electronic Image Detectability Under Varying Illumination Conditions, Jeremy J. Miller

Theses and Dissertations

Light in the built environment plays an essential role in the vision and the health of humans through non-visual receptors in the eyes. Unfortunately, image analysts and other Air Force personnel who engage in the detection of objects on softcopy displays are often required to work in very dimly-lit or dark environments as higher illumination reduces the contrast of displayed information. Literature has shown that increases in light exposure improves circadian rhythm entrainment and reduces the negative health consequences of insufficient lighting. This research examines the effects of indoor lighting to determine if increases in ambient illumination or changes to …