Applied Mathematics Commons^™

Agent-Based Dynamics Of A Spahr Opioid Model On Social Network Structures, Owen Queen, W. C. Strickland, Leigh B. Pearcy

Chancellor’s Honors Program Projects

No abstract provided.

Toward Suicidal Ideation Detection With Lexical Network Features And Machine Learning, Ulya Bayram, William Lee, Daniel Santel, Ali Minai, Peggy Clark, Tracy Glauser, John Pestian

Northeast Journal of Complex Systems (NEJCS)

In this study, we introduce a new network feature for detecting suicidal ideation from clinical texts and conduct various additional experiments to enrich the state of knowledge. We evaluate statistical features with and without stopwords, use lexical networks for feature extraction and classification, and compare the results with standard machine learning methods using a logistic classifier, a neural network, and a deep learning method. We utilize three text collections. The first two contain transcriptions of interviews conducted by experts with suicidal (n=161 patients that experienced severe ideation) and control subjects (n=153). The third collection consists of interviews conducted by experts …

A Meshless Approach To Computational Pharmacokinetics, Anthony Matthew Khoury

Doctoral Dissertations and Master's Theses

The meshless method is an incredibly powerful technique for solving a variety of problems with unparalleled accuracy and efficiency. The pharmacokinetic problem of transdermal drug delivery (TDDD) is one such topic and is of significant complexity. The locally collocated meshless method (LCMM) is developed in solution to this topic. First, the meshless method is formulated to model this transport phenomenon and is then validated against an analytical solution of a pharmacokinetic problem set, to demonstrate this accuracy and efficiency. The analytical solution provides a locus by which convergence behavior are evaluated, demonstrating the super convergence of the locally collocated meshless …

On Efficacy And Effectiveness Of Vaccines: A Mathematical Approach Based On Conditional Probability With Applications To The Covid-19 Context, Flavius Guias

Spora: A Journal of Biomathematics

This paper presents a mathematically formalized approach which points out the relation between efficacy and effectiveness of vaccines. The first term denotes the relative degree of protection in clinical trials or under ideal conditions, while the latter is based on observed real-life data. We define the efficacy by a similar formula to the effectiveness, but the probabilities involved in the relative risk are conditional with respect to the exposure to the virus. If exposure and vaccination status are independent, the two quantities are equal. Otherwise, the observed value of the effectiveness is a biased one, as it could be seen …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Poster Session, Emma Beeler, Maddison Caldwell, Mackenzie Paul, Shirli Salihaj, Sara Lynn Sligh, Stephen Trest

Mississippi Undergraduate Honors Conference

Video provided is of MacKenzie Paul's presentation.

Abstracts

Humanities

Emma Beeler, Mississippi University for Women

Adultery and Fidelity in the Lais of Marie de France

Using both literary and historical analysis, I will examine contrasting depictions of adultery and fidelity within the lais written by 12th-century poet Marie de France. A lai is a type of narrative poem, ranging in length from 118 to 1184 lines. Many of Marie de France’s lais follow the literary trope known as courtly love; however, the reader is encouraged to sympathize with different characters depending on the lai. In some lais, the reader …

An Exploration In Health Analytics: Pediatric Burns, Care Policy Assessment And Interrupted Time Series, Chao Wang

2022

Healthcare systems globally face multiple challenges in the face of population growth and changes in disease pathology. With regard to the rising demand of the healthcare and the global threats of the pandemic, the medical datasets can be trained further to develop preventive methods. Meanwhile, policy reforms of health systems could be a critical aspect to deal with the public crisis and concerns. However, two basic problems must be addressed first: identification of key factors on a priority basis and evaluation of changes.

Thus, the paper presents a series of trials on the application of data analytics to health-related problems, …

Electroencephalogram Classification Of Brain States Using Deep Learning Approach, Hrishitva Patel

Computer Science Faculty Scholarship

The oldest diagnostic method in the field of neurology is electroencephalography (EEG). To grasp the information contained in EEG signals, numerous deep machine learning architectures have been developed recently. In brain computer interface (BCI) systems, classification is crucial. Many recent studies have effectively employed deep learning algorithms to learn features and classify various sorts of data. A systematic review of EEG classification using deep learning was conducted in this research, resulting in 90 studies being discovered from the Web of Science and PubMed databases. Researchers looked at a variety of factors in these studies, including the task type, EEG pre-processing …

Covid-19 Collaborative Modelling For Policy Response In The Philippines, Malaysia And Vietnam, Angus Hughes, Romain Ragonnet, Pavithra Jayasundara, Hoang-Anh Ngo, Elvira P. De Lara-Tuprio, Ma. Regina Justina Estuar, Timothy Robin Y. Teng, Law Kian Boon, Kalaiarasu M. Peariasamy, Zhuo-Lin Chong, Izzuna Mudla M. Ghazali, Greg J. Fox, Thu-Anh Nguyen, Linh-Vi Le, Milinda Abayawardana B. Eng, David Shipman, Emma S. Mcbryde, Michael T. Meehan, Jamie M. Caldwell, James M. Trauer

Mathematics Faculty Publications

Mathematical models that capture COVID-19 dynamics have supported public health responses and policy development since the beginning of the pandemic, yet there is limited discourse to describe features of an optimal modelling platform to support policy decisions or how modellers and policy makers have engaged with each other. Here, we outline how we used a modelling software platform to support public health decision making for the COVID-19 response in the Western Pacific Region (WPR) countries of the Philippines, Malaysia and Viet Nam. This perspective describes an approach to support evidence-based public health decisions and policy, which may help inform other …

Mathematical Models Of Infection Prevention Programs In Hospital Settings, Kelly A. Reagan

Theses and Dissertations

Hospitals play a vital role in providing for the healthcare needs of a community. Patients can develop hospital-acquired infections (HAIs) during their hospitalization due to exposure to foreign bacteria, viruses, and fungi. Infection prevention programs target and reduce HAIs, but implementing the infection prevention programs often comes with a cost. The goal of my research is to use mathematical models to quantify the impact of infection prevention programs on cases of HAIs and total healthcare costs. First, I use a Markov chain model to quantify how one infection prevention program reduces general HAIs in the hospital. Then, I calculate the …