Digital Commons Network^™

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 = …

Detecting Early Operational Turbulence In The Emergency Department Using Fourier And Wavelet Analysis: A Conceptual Framework For Signal-Informed Anticipation And Prediction In The Ed Complex Adaptive System, James Espinosa, David Ho, Alan Lucerna

Rowan-Virtua Research Day

Background:

We theorize that Emergency Departments (EDs) function as complex adaptive systems characterized by nonlinear interactions, oscillatory demand patterns, and abrupt phase transitions from stable flow to turbulent states. Traditional dashboards rely on threshold metrics that detect instability after degradation becomes visible. Many ED data streams are significantly retrospective as well as compression-averaged into temporal systems such as days, months, quarters or even years. Signal processing methods—particularly Fourier and wavelet analysis—offer the  framework for detecting latent oscillatory shifts preceding overt operational change from laminar to transitional to turbulent flow states. This could lead to better methods of adaptation.

Conceptual Framework: …

Designing Patient Update Intervals In The Emergency Department: A Queueing-Theory And Operational Science Model Of Patient Updates And Progress Signaling To Improve Patient Experience, James Espinosa, Alan Lucerna, Henry Schuitema

Rowan-Virtua Research Day

Background Patients in the Emergency Department (ED) frequently experience uncertainty while awaiting diagnostic results, reassessment, and disposition. Even when clinical processes are progressing, prolonged informational silence may create the perception of that those processes are not advancing.

Objective To develop a conceptual and operational mathematical, queuing-theory based  model linking bedside communication, conversational time, and informational silence to patient experience.

Methods A back-of-the-envelope operational model was constructed to estimate the time required for bedside update communication during a typical physician shift. A queueing-theory framework was applied to examine how intervals between informational updates influence perceived waiting burden. Concepts from queueing theory …

In School Age Children With Autism Spectrum Disorder, Does Academic Achievement And Social Development Improve In Inclusive Classroom Environments?, Ashley A. Macquaid

Rowan-Virtua Research Day

Autism Spectrum Disorder (ASD) is a developmental disorder characterized by difficulties in social skills, communication, and sensory processing 1. ASD affects approximately 1 in 100 children internationally 2. With the growing prevalence, classroom inclusivity of individuals with autism has emerged as a priority in education. However, current literature presents a range of positive and negative factors without clear indication of effective classroom placement for students' specific needs. This research aims to determine if inclusive classroom environments improve academic achievement and social development for school-age children with ASD. A systematic search on PubMed, Embase, and Cochrane databases yielded studies published between …

Evaluating The 4mm Endometrial Thickness Threshold: Racial Disparities In Ultrasound Sensitivity And Diagnostic Delay, Ngozi Ikpeama, Sophia Vogiatzidakis, Xuezhi Jiang, Elizabeth Hertz, Vitoria Chaves, Peter Schnatz

Rowan-Virtua Research Day

Title: Evaluating the 4mm Endometrial Thickness Threshold: Racial Disparities in Ultrasound Sensitivity and Diagnostic Delay

Background: Current ACOG guidelines utilize a 4mm endometrial thickness (ET) threshold via transvaginal ultrasound (TVUS) to exclude malignancy in postmenopausal women. However, recent evidence suggests these standardized thresholds may not be equally effective across all racial cohorts. This systematic review evaluates the diagnostic performance of the 4mm threshold specifically in Black patients.

Methods: A systematic search of peer-reviewed literature was conducted to identify studies comparing TVUS sensitivity and clinical outcomes between racial groups. Data were extracted focusing on the diagnostic sensitivity of the 4mm threshold, …

A Retrospective Chart Review: Screening Patients With Type 2 Diabetes For Depression, Jennifer Sheldon, Glynnis Haley, Monica Ketchie

The Corinthian

Type 2 Diabetes Mellitus is defined as an impaired production of insulin resulting in elevated blood glucose levels (Brutsaert E., 2020). Globally, approximately 8% to 9% of adults have diabetes mellitus, the majority of which (95%) have Type 2 Diabetes Mellitus, equating to between 624 million to 702 million people (WHO, 2020). Type 2 Diabetes Mellitus represents the seventh leading cause of death, with approximately 1.5 million new cases diagnosed annually in the United States (CDC, 2020).

Depression is clinically defined as a mental health disorder that presents with a continually depressed mood or a loss of interest in daily …

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 …

Genealogy-Based Trait Association With Locater Boosts Power At Loci With Allelic Heterogeneity, Xinxin Wang, Ryan Christ, Erica Young, Chul Joo Kang, Indraniel Das, Edward A Belter, Markku Laakso, Louis J M Aslett, David Steinsaltz, Nathan O Stitziel, Ira M Hall

2020-Current year OA Pubs

A key methodological challenge for genome-wide association studies is how to leverage haplotype diversity and allelic heterogeneity to improve trait association power, especially in noncoding regions where it is difficult to predict variant impacts and define functional units for variant aggregation. Genealogy-based association methods have the potential to bridge this gap by testing combinations of common and rare haplotypes based purely on their ancestral relationships. In parallel work, we have developed an efficient local ancestry inference engine and a novel statistical method (LOCATER) for combining signals present on different branches of a locus-specific haplotype tree. Here, we develop a genome-wide …

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 …

Implementation Of Wellness Activities In An Experiential Rotation To Promote Pharmacy Student Well-Being, Neeloufar Fakourfar, Brenda Kilzi, Reza Taheri, Richard Beuttler, Hindu Rao

Pharmacy Faculty Articles and Research

Background

Educational activity

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 …

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 …

Ai×Life 2026: Advances In Computational Biology Across Scales For Life & Health Sciences, Suma Mohan S., Devika N. T., Pranavathiyani G.

Conference Proceedings

Book of Abstracts of the International Conference, AIxLife 2026: Advances in Computational Biology Across Scales for Life & Health Sciences, held on 17–18 April 2026, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, INDIA 

About the Conference

Conventional computational biology laid the foundation for biological data analysis through statistical models, algorithms, and curated databases, enabling insights into genes, proteins, and pathways. Today, the integration of artificial intelligence, spanning machine learning, deep learning, and large language models (LLMs) is driving a transformative shift across biological scales, from atomic and molecular interactions to pathways, cellular systems, organisms, and populations.

AI-powered approaches …

Addressing Socioeconomic Factors Related To Health Disparities In Predominantly Hispanic Texas Communities, Gabriela M. Gomez

Theses & Dissertations

This qualitative study examined the socioeconomic factors that influenced health outcomes in predominantly Hispanic Texas communities in San Antonio, Texas. Few studies have been conducted that address how socioeconomic conditions have shaped the lives of the Hispanic population in Texas, indicating a significant gap in the research. The research question guiding this study asked: How do Hispanic individuals between the ages of 26 and 64 who live in predominantly Hispanic communities describe health disparities in San Antonio, Texas? To address the research question, a qualitative inquiry was conducted using semi-structured in-person interviews with participants who met the inclusion criteria. A …

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

Immersive Visualization Of Cardiac Segmentation And Analysis, Brandon Norman

Theses and Dissertations

Coronary artery disease remains one of the leading causes of death worldwide, making early detection and treatment critical to reducing mortality. While coronary angiography remains the gold standard procedure for diagnosing coronary artery disease, less invasive methods such as coronary computed tomography angiography and virtual fractional flow re-serve continue to improve. However, taking full advantage of volumetric coronary computed tomography angiography data requires extensive post-processing before the data can support geometric modeling, hemodynamic simulation, and analysis. Existing Open-Source Appli-cations provide powerful tools for these tasks, but their interaction models remain largely desktop based, restricting users to 2d manipulation and hindering …

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 …