Physical Sciences and Mathematics Commons^™

Replication And Extension Of Kras-Associated Gene Expression Signatures In Lung Adenocarcinoma: A Cox Proportional Hazards Analysis Of Mutation Status, Gene Expression, Multi-Gene Mutation Count, And Ras De Novo Signature, Camryn Berry

Theses & Dissertations

This study evaluates the robustness and reproducibility of a previously published analysis of lung adenocarcinoma gene expression data (Schabath et al.), which examined KRAS-associated biology in relation to co-occurring STK11 and TP53 mutations. The original study used Kaplan-Meier (KM) survival analysis and gene expression signatures to assess associations between driver mutations, tumor suppressor mutations, and patient outcomes. The aim of this work is to replicate these analyses and evaluate consistency across independent datasets (Wilkerson and Selamat), with extension using Cox proportional hazards (PH) models. Two hypotheses are evaluated: (1) that the number of mutated genes increases the hazard of death, …

The Influence Of Fermentation Duration And Secondary Fermentation Conditions On The Bioactive Compound Profile Of Kombucha, Jordan Vereen

Honors Theses

Kombucha is a fermented sweet tea produced using a symbiotic culture of bacteria and yeast (SCOBY) and has gained widespread popularity due to its proposed health benefits. Kombucha has been studied to understand these advantages in cardiovascular support, improved metabolism, increased antioxidant effects, enhanced antimicrobial properties, and even potentially slowing the progression of certain diseases. Despite its increasing popularity, the way in which the specific bioactive compounds responsible for these effects and the fermentation conditions that influence their production remain unclear. The present study, conducted in collaboration with Dr. Budner, focuses on quantifying bioactive compounds in kombucha to better understand …

The Legacy Of Lead: Lead Exposure's Harmful Effects And Its Concentration In Poc Communities, Layla Sophronia Barber

Student Theses 2015-Present

This thesis examines the disproportionate burden of lead exposure carried by low income, POC communities. The systemic nature of this problem is a symptom of a longstanding legacy of environmental injustice in the United States. Decades of federal neglect are reflected in the higher statistics of lead exposure and poisoning in predominantly black communities. While it is understood that lead exposure poses a serious threat to physical health and early cognitive development, there is a discouraging lack of urgency to remove the toxin from non-wealthy communities. The material covered by this thesis aims to identify and correct the discriminatory social …

Assessing Trends In Medical Students’ Perceptions Regarding Statistical Analysis, Ethan Noble, Valeriy Kozmenko, Paul Thompson

Scholarship Pathways Program

Assessing Trends in Medical Students’ Perceptions Regarding Data Analysis and Statistics Knowledge and Skills

Ethan Noble, MD | Mentors: Valeriy Kozmenko, MD, Paul Thompson, PhD

Introduction: The use of evidence-based medicine requires that physicians are able to properly analyze and interpret the results of new research. The development of new research and medical knowledge is swift, and a strong foundation in statistics and research is needed for physicians and medical students to keep up with new research. Curriculum in medical education often lacks in-depth coverage of the subject, and additional curriculum has been shown to enhance student confidence and ability …

Table Of Contents

Journal of the South Carolina Academy of Science

No abstract provided.

Psychiatry Meets Ai: Are Residents Ready?, Jacob De Castro, John Case

Rowan-Virtua Research Day

Artificial intelligence (AI) use is increasing in healthcare, but psychiatry residency training remains unstructured. In a 20-resident pilot survey, AI was frequently used for literature review and clinical support, with limited confidence and institutional guidance. We found most residents desired formal training and would use AI more if institutionally supported. Findings highlight a gap between rapid adoption and structured education.

Ai-Augmented Digital Auscultation For Point-Of-Care Screening Of Valvular Heart Disease: A Systematic Review And Meta-Analysis, Harshal Parmar, Akhila Archakam, Nikhila Archakam, Wesley Kim, Eduard Koman Md

Rowan-Virtua Research Day

Background: Valvular heart disease (VHD) affects >10% of adults aged 75+ yet remains underdiagnosed when asymptomatic due to declining auscultatory proficiency. AI-augmented digital auscultation offers a point-of-care screening solution, though no meta-analysis has pooled diagnostic accuracy across VHD subtypes in adults using echocardiography as the reference.

Methods: A systematic review and meta-analysis were conducted per PRISMA guidelines. PubMed, Embase, Cochrane, IEEE Xplore, and Scopus were searched without date restriction. Studies applying AI or machine learning to digital auscultation or phonocardiography for VHD classification in adults with echocardiographic reference and patient-level diagnostic metrics were included. Studies using only public datasets, pediatric …

Developing A Comprehensive Resource Guide For Caregivers Within The Area Agency On Aging, Aiden R. Murphy

Public Health Capstone Projects

This project developed a new universal caregiver resource guide for caregivers within the Area Agency on Aging, in order to improve resource navigation and workflow efficiency. Resources were collected, verified, and organized into a new, streamlined guide via the ARIA chatbot, covering multiple needs. Caregiver resources were collected and verified by the capstone student and mentor, Michael Kroeker, and organized into a centralized knowledge base within the ARIA chatbot. A mixed methods evaluation was conducted utilizing a 5-point Likert scale with three quantitative questions and one open-ended qualitative question. The data was given to the SeniorLine staff, who wanted to …

Air Quality, Atmospheric Pressure, And Migraine Presentations In The Emergency Department, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

Background: Migraine is a leading cause of Emergency Department (ED) visits and global disability. Weather has long been reported by patients as a trigger, yet the literature remains inconsistent. Prior ED-based data demonstrated an association between higher mean barometric pressure and increased migraine presentations, without a relationship to short-term pressure change. Because high-pressure systems are frequently associated with atmospheric stagnation and pollutant accumulation, air quality may represent a biologically plausible mediator.

Objective: To examine the relationship between air quality and ED migraine presentations within the existing body of literature and to explore whether air quality may help explain previously observed …

Listening To The System: Reframing Emergency Department Noise: The Case For Noise As A Real-Time Operational Signal In A Complex Adaptive System (Cas), James Espinosa, Alan Lucerna, Henry Schuitema

Rowan-Virtua Research Day

Emergency Department (ED) noise has historically been framed as an occupational and environmental hazard requiring mitigation. And this is still true—but not complete. Early work focused on exposure reduction and spike identification. Subsequent mapping studies demonstrated spatial and temporal differentiation in ED acoustic load. We propose an expanded conceptual model: acoustic variability may function not only as a hazard, but also as a real-time signal of operational turbulence within the ED as a complex adaptive system (CAS). Drawing on human factors, alarm fatigue, resilience engineering, and complexity science, we synthesize existing literature and institutional experience to identify a critical gap—noise …

The Physics And Biology Of High-Risk Falls: Biomechanical Analysis And Physics Assists In Understanding Why The Threshold For High-Risk Was Lowered To 10 Feet, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

Background: Recent revisions to the National Guideline for the Field Triage of Injured Patients lowered the high-risk fall threshold from >20 feet  to >10 feet for all ages. Guideline changes are multifactorial and typically reflect epidemiologic registry data, injury severity trends, and systems-level performance feedback. However, biomechanical analysis assists in understanding the importance of the change.

Objective: To demonstrate that a 10-foot fall generates sufficient kinetic energy and deceleration forces to exceed structural tolerance thresholds in multiple human tissues, and to show that fundamental physics independently supports the recent trauma protocol change.

Methods: Application of gravitational motion equations (v = …

Predicting And Decoding Allosteric Binding Sites Using Protein Language Models And Structure-Based Machine Learning: An Energy Landscape-Guided Explainable Ai Framework, Kamila Riedlová, Vít Skrhák, William G. Gatlin, Max Ludwick, Lucas Turano, Marian Novotný, David Hoksza, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Computational prediction of allosteric binding sites in protein structures remains a persistent challenge, as these regulatory pockets evade detection by both sequence-based and structure-based algorithms. Both computational and physical origins of this predictive asymmetry remain insufficiently understood. In this study, we systematically examine the determinants of binding site predictability using a dual framework that integrates a fine-tuned protein language model and the structure-based method P2Rank as complementary tools probing a diverse data set of 453 human kinases, together with a physics-based interpretability layer derived from energy landscape frustration analysis. Both predictors exhibit a sharp and reproducible dichotomy on protein kinases, …

Freshman 15? Freshman 50?? The Reality Of Daily Life Habits Of A First Year College Student, Gregorio R. Salgado

Student Scholar Symposium Abstracts and Posters

This project presents a personal data tracking study in which I collected daily self-reported metrics over the course of the Spring semester using Excel. The variables tracked include sleep duration, caloric intake, screen time, social media usage, phone checks per day, family communication, and personal spending. The goal of this project is to identify meaningful patterns and correlations between daily habits and personal well-being.

Data was collected through a combination of manual logging and smartphone-generated daily reports. This study explores potential relationships between variables such as sleep duration and social media usage, as well as the association between family communication …

Herbularyo (Folk Healer): An Herbal Medicine Card Game, Maryjane T. Magsino, Inah Marie Q. Rivera, Armando M. Guidote, Genejane M. Adarlo

Chemistry Faculty Publications

Herbularyo, a card game teaching about herbal plants (HPs), was created and evaluated as a viable educational card game based on Tuomisto and Aksela’s criteria. A quasi-experiment was performed on 81 Grade 8 students from a private high school and 50 Grade 11 from a public high school. Independent t-test revealed that the control group (CG) and experimental group (EG) (p=0.386), and EG1 (played ≤5) and EG2 (played >5) (p=0.681) are not comparable with each other. Paired t-test showed EG performed better (p=0.001) than CG (p=0.901) whereas ANCOVA showed that playing Herbularyo improved students’ information retention (p=0.006). EG1 and EG2 …

Automated Analysis Of Radiation Oncology Incident Reports Using Large Language Models, Nathan A. Dobranski

LSU Master's Theses

Patient safety incident reporting in radiation oncology requires expert analysis that is time-intensive and subject to variability. This thesis presents the development and technical validation of a locally deployed large language model (LLM) system for automated incident report analysis across multiple cancer centers. The system was designed for automated summarization and taxonomy assignment of Radiation Oncology Incident Learning System (RO-ILS) reports, operating entirely on local infrastructure to preserve patient privacy. A two-round, multi-rater evaluation methodology was employed, incorporating 600 total expert evaluations from two academic cancer centers. Round 1 established baseline performance using Mistral 7B and Mixtral 8x7B models with …

Faircarenlp: An Ai-Driven Patient Review Analyzer For Healthcare, Sayyed Mohammad Pourya Momtaz Esfahani, Davey Seeman, Christoffer Dharma, Mohammad Noaeen, Shion Guha, Zahra Shakeri

Health Services and Informatics Research

Objective

To develop and evaluate an automatic patient review analyzer that applies advanced Natural Language Processing (NLP) and machine learning methods to improve the efficiency, fairness, and accuracy of healthcare feedback analysis.

Materials and methods

We designed a multi-component pipeline incorporating sentiment analysis, key theme extraction, clinical Named Entity Recognition (NER), and fairness modules. Bias mitigation was addressed through the integration of three complementary approaches: adversarial debiasing, Hard Debiasing, and Iterative Null-space Projection (INLP). Multiple BERT-based models (DistilBERT, BioBERT, RoBERTa-base, BERT-base-uncased) were trained and evaluated under varying hyperparameters and fairness/adversarial loss configurations. Model performance was assessed using accuracy, F1, recall, …

Ais26s: Ai In Biomedicine, Shiqian Shen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation explores the role of artificial intelligence in advancing biomedical research and clinical practice from the perspective of a physician-scientist. Dr. Shiqian Shen discusses current challenges in neuroscience and medicine, including limitations in human observation, data analysis, and decision-making across complex biological systems. The talk highlights how AI-driven approaches such as computer vision, neural signal processing, and large-scale data modeling can improve the understanding of disease mechanisms, enhance experimental workflows, and enable more precise, patient-centered care. Specific applications include automated classification of neural activity, behavioral analysis in animal models, and multimodal data integration. A key concept introduced is “shadow …

Volume 17, Christian O’Neill, Kyara Greene, Savva Sidorov, Laura Bisaillon, Luke Clemmer, Hannah Gordon, Kitt Benson, Taylor Blount, Rachel Danzitz, Nicholas Duellman, Chase Gionis, Hima Fernando, Seth Franzyshen, Onyx Gonzalez, Bryan Lin, Samantha Start, Ysabel Wells, Maggie Duncan

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Cover Artist’s Statement Maggie Duncan

On Mentoring Dr. Yulia Uryadova

Ukrainian Resistance in the Face of Russification: Nestor Makhno and Anarchism

by Christian O’Neill

Life Vest by Kyara Greene

Isolation and 16S rRNA Identification of Bacteria from Fire Department Connection Pipe by Savva Sidorov

The Effectiveness of Planned Exercise in Reducing ADHD Symptoms in Children by Laura Bisaillon & Luke Clemmer

Linguistic Analysis on Confidence and Communication Strategies with Disparities Between Sign Fluency and Hearing Impairment by Hannah Gordon

Freedmen in Indian Territory by Kitt …

Understanding Delays In Emergency Department Care: A National Analysis Of Wait Times, Gregory Forsberg

Mathematics, Statistics, and Computer Science Honors Projects

Emergency department (ED) wait times remain a persistent bottleneck in the United States healthcare system, impacting patient outcomes, hospital efficiency, and equitable access to care. This study analyzes nationally representative data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a complex, multi-stage probability sample. Using survey-weighted analyses and predictive modeling, we examine the effects of patient characteristics, triage acuity, and visit timing. Results indicate that operational and system-level factors, including hospital capacity, geographic region, and temporal variation, are among the most influential predictors of ED wait times

Evaluation Of The Effectiveness Of Antihypertensive Therapy Chosen Through Maternal Hemodynamic Profile Analysis, Margaret Weimer

Poster Presentations

In treatment of emergent hypertension, the American College of Obstetricians and Gynecologists (ACOG) recommends both oral labetalol and nifedipine, with no preference shown between the two. These medications have different mechanisms of action. Studies have suggested that consideration of hemodynamic profile may be an effective way to determine medication, but have not considered the Rule of 55, a simple calculation to predict hemodynamic profile.

Goals: 1. Determine if tailoring the antihypertensive to patient’s hemodynamic profile is associated with better control of blood pressure. 2. Determine if the Rule of 55 is an accurate method to determine hemodynamic profile.

From Data Digitization To Personalized Care: Deep Learning And Decision Analytics In Healthcare Systems, Ahla Ko

Graduate Theses and Dissertations

This dissertation traces a progression from foundational data infrastructure to individualized clinical decision-making, developing and evaluating three computational frameworks that advance healthcare efficiency and personalization through deep learning and decision analytics. The first study presents an end-to-end pipeline for automated recognition of handwritten medical forms, addressing persistent challenges in health data digitization. Integrating a YOLO-based field detection model, a Convolutional Recurrent Neural Network (CRNN) for text transcription, and a confidence-based human-in-the-loop quality assurance framework, the system achieved 99.75\% Exact Match Accuracy and a 0.13\% Character Error Rate on medical forms collected from a tuberculosis research project in Moldova. A GPU-accelerated …

Barriers To Climate Change And Sustainability Action: Nursing Education And Practice, Dawn Marie Smith

Dissertations

Climate change is one of the most pressing public health emergencies of our time and nurses can have a great impact in their current practice and in the education of future nurses (The Alliance of Nurses for Healthy Environments, n.d.; American Nurses Association, 2023; Health Care without Harm, 2025). Deaths due to rising temperatures, vector-borne illness, and food insecurity related to drought and extreme weather are on the rise (WHO, 2024). It has been estimated that globally over 250,000 additional deaths will be attributed to climate related effects between 2030 and 2050 (Watts et al., 2020; WHO, 2023).

A primary …

Engineering Silicone Magnetic Fluids For Localized Radiation Attenuation During Ocular Melanoma Brachytherapy, Zachary L. Caprow

All Dissertations

Ocular melanoma is commonly treated using plaque brachytherapy; however, radiation-induced damage to healthy ocular tissues frequently results in partial or complete vision loss. This work investigates the development of an injectable, magnetically responsive silicone magnetic fluid designed to localize adjacent to the tumor and attenuate low-energy gamma radiation during treatment.

The material system consists of iron oxide nanoparticles surface-functionalized with a siloxane polymer, in which the nanoparticles provide magnetic responsiveness and radiation attenuation, while the polymer coating ensures colloidal stability, injectability, and biocompatibility. A one-pot synthetic approach was developed wherein a functionalized siloxane polymer containing iron-affinitive groups was reacted with …

Utilizing Brain Computer Interfaces That Interact With A Virtual Keyboard, Skye Lilienthal

Honors Theses

A brain-computer interface (BCI) can allow someone to utilize electrical signals in their brain to complete tasks using a computer. BCIs can help people take advantage of technology to type without the need for a traditional keyboard setup. This paper used the OpenBCI Mark IV to test the effectiveness of non-invasive BCIs with dry electrodes within the OpenViBE P300 Speller. This paper shows how to use the P300 speller through a setup pipeline. Results indicate that electrode placement affects P300 accuracy and that areas related to visual processing improve accuracy, suggesting that P300 signals can be detected within OpenBCI Mark …

Building Dental Workforce Pathways In A Rural State Without A Dental School, Rashid Ahmad, Shawnda Schroeder

Indigenous Health Posters and Presentations

In North Dakota, workforce shortages are shaped by geography, training pathways, and weak return incentives.

• Statewide Dental Health Professional Shortage Area designation
• No in-state dental school
• Workforce shortages function as a structural driver of inequity • Oral health disparities among children, low-income populations, and Indigenous communities

Smart Medical Support System And Swin Transformer Framework For Breast Cancer Detection And Segmentation In Mammograms, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Accurate and reliable breast cancer detection from mammographic images remains a critical challenge due to subtle lesion appearance, high intra-class variability, and class imbalance inherent in clinical datasets. To address these issues, this study proposes Swin-BreastNet, an explainable and optimization-driven deep learning framework for binary classification of benign and malignant breast lesions from full-field digital mammograms. The proposed approach leverages the hierarchical Swin Transformer model to effectively capture fine-grained local texture patterns and long-range contextual dependencies through Shifted Window Multi-head Self-Attention (SW-MSA). A key novelty of this work lies in the integration of Harris Hawks Optimization (HHO) for automated hyperparameter …

Public Health Responsible Ai Capability (Ph-Raic) Framework: A Conceptual Model For Integrating Ai Into Public Health Agencies, Arnob Zahid, Ravishankar Sharma, Rezwan Ahmed

All Works

Background: Artificial intelligence (AI) is transitioning from experimental pilots to core public health functions such as disease surveillance, resource planning, and analysis of social and structural determinants of health. Yet, health data collection and stewardship remain fragmented across the globe; some jurisdictions still rely on paper-based systems, while others operate noninteroperable digital systems that can exacerbate inequities. Treating health data as a global good therefore requires governance that enables innovation while protecting rights, safety, and trust. This study aims to develop a conceptual meso-level capability framework that translates responsible AI principles into organizational practices for public health agencies. Methods: We …

Factors Affecting Pedestrian-Vehicle Conflicts: An Empirical Analysis, Christo D. Jamo

Honors Scholar Theses

The number of pedestrian deaths increased by 78% between 2009 and 2023, while other motor vehicle crash deaths increased by 13% in the same period [1]. To identify potential pedestrian safety measures, this study analyzed the effects of location-based demographics, pedestrian phasing type, and other physical infrastructure and behavior variables on the probability of pedestrian-vehicle conflicts at signalized intersections, which is a surrogate measure of crash risk. Data were collected from 55 intersections in Connecticut, and the pedestrian-vehicle interactions were classified by severity based on the Swedish Traffic Conflict Technique: undisturbed passage, potential conflict, minor conflict, or serious conflict. Because …

Stochastic Universal Differential Equations For Epidemiological Modeling: Uncertainty Quantification In Disease Transmission Dynamics, Alice Menaya Armah-Bonney

Electronic Theses and Dissertations

Epidemic forecasting requires not only predictions of expected case counts, but also quantification of uncertainty, although existing surrogate modeling frameworks for agent-based models remain fundamentally deterministic. In this thesis a Stochastic Universal Differential Equation framework is presented that extends the deterministic Universal Differential Equation approach by incorporating a learnable stochastic diffusion term, enabling calibrated probabilistic forecasts while preserving the mechanistic interpretability and computational efficiency of the deterministic baseline. In doing so, a two-phase training algorithm is introduced to ensure stable convergence and the framework is validated against the ensemble output from ExaEpi, an exascale agent-based model of a COVID-19 outbreak …

Pattern Dynamics And Stochasticity Of Brain Rhythms And Spike Trains In A Tauopathy Mouse Model Of Alzheimer’S Disease, Clarissa M. Hoffman

Dissertations and Theses (Open Access)

Systems neuroscience posits that every aspect of perceived physical reality, every aspect of animal and human behavior, and every cognitive phenomenon emerges from patterns of neuronal activity. While most researchers embrace this idea, there are major difficulties in describing and analyzing these complex neuronal dynamics—spike flows produced by cells ensembles, synchronized extracellular field oscillations, and other patterns—which limits our understanding of how the activity of individual neurons and the whole-animal cognition and behavior might be connected. In particular, we lack the approaches and even the semantics for connecting the individual cell outputs and the integrated results of their activity. Current …