Digital Commons Network^™

Qualitative And Quantitative Analysis Of A Novel Dental Health Education Program To Improve Dental Care Utilization By Bhutanese-, Burmese-, And Swahili-Speaking Refugees In A Midwestern United States City, Chandra Swanson, Katherine Gordon, Kelly Kreisler, Elizabeth Montgomery Collins

2020-Current year OA Pubs

No abstract provided.

Adapting Data Science Competencies By Role And Purpose: Voice Ai, David A Dorr, Andrea Krussel, Rachel Hauck, Christie Jackson, Abhijeet Dalal, Steven Bedrick, Philip R O Payne, Bridge2ai-Voice Consortium;, William Hersh

2020-Current year OA Pubs

Competencies help define the skills and knowledge needed by learners. Often broad, educators integrate competencies to provide a framework for curricula or professional standards. For data science, the rate of change in the field, role variations, and specificity in key applications can be challenging. Our objective was to adapt general data science competencies for different learner roles in an emerging area: the clinical utility of Voice, Language, and Speech-based Artificial Intelligence/Machine Learning (AI/ML). Using a persona-inductive approach, we adapted competencies to support learners from varying professional and educational backgrounds and implemented these adaptations in a multi-institutional summer school. Results from …

Applications Of Quantum Computing In Clinical Care, Stevan C Fairburn, Lara Jehi, Brenton T Bicknell, Beckley G Wilkes, Bharat Panuganti

2020-Current year OA Pubs

INTRODUCTION: This review examines quantum computing (QC) applications in clinical care, emphasizing advancements directly impacting patient outcomes. QC holds transformative potential in medicine, particularly through enhancing diagnostic accuracy, optimizing treatment plans, and enabling real-time decision-making.

METHODS: A systematic analysis of 35 studies published between 2015 and 2024 was conducted. The studies were evaluated for their contributions to diagnostic, therapeutic, and decision-support improvements in clinical care enabled by quantum computing technologies.

RESULTS: The analysis revealed QC's promise in improving diagnostic accuracy in medical imaging, optimizing treatments in oncology, and enhancing real-time clinical decision-making. QC-driven algorithms demonstrated potential to enhance diagnostic accuracy …

Zika Virus Encephalitis Causes Transient Reduction Of Functional Cortical Connectivity, Shannon C Agner, Lindsey M Brier, Jeremy D Hill, Ethan Y Liu, Annie Bice, Rachel M Rahn, Shengxuan Chen, Joseph P Culver, Robyn S Klein

2020-Current year OA Pubs

SIGNIFICANCE: Determining the long-term cognitive impact of infections is clinically challenging. Using functional cortical connectivity, we demonstrate that interhemispheric cortical connectivity is decreased in individuals with acute Zika virus (ZIKV) encephalitis. This correlates with decreased presynaptic terminals in the somatosensory cortex. During recovery from ZIKV infection, presynaptic terminals recover, which is associated with recovered interhemispheric connectivity. This supports the contribution of synapses in the cortex to functional networks in the brain, which can be detected by widefield optical imaging. Although myeloid cell and astrocyte numbers are still increased during recovery, RNA transcription of multiple proinflammatory cytokines that increase during acute …

Development Of An Ecg-Based Deep Learning Model For Pediatric Congenital Heart Disease (Chd) Diagnosis, Annbar Mekouar

Selected Full-Text Master Theses 2021-

Congenital heart disease (CHD) stands as the leading congenital anomaly which affects pediatric populations throughout the world. The effectiveness of treatment depends on both early diagnosis and accurate identification but echocardiography requires manual interpretation which proves time-consuming and inconsistent especially when examining pediatric patients with their distinct cardiac systems. The research aims to create a deep learning-based diagnostic framework which uses ECG data to identify coronary artery disease subtypes in pediatric patients. The model uses high-quality datasets from Dr. Ignacio Lugones to extract R-R intervals and QRS durations through convolutional neural networks (CNNs). The system addresses pediatric-specific challenges while enhancing …

Adverse Childhood Experiences, Depression And Subjective Cognitive Decline By Gender: A Moderated Mediation Analysis, Monique J. Brown, Darlingtina K. Esiaka, Jaya Viswanathan

Behavioral Science Faculty Publications

Studies assessing depression as a mediating factor between adverse childhood experiences (ACEs) and subjective cognitive decline (SCD) are lacking. Therefore, the aims of this study were to: (1) determine the mediating role of depression in the association between ACEs and SCD; and (2) assess the moderating role of gender. Data were obtained from the 2023 Behavioral Risk Factor Surveillance Study (BRFSS) survey (N = 38,600). Crude and adjusted path analyses were used to determine the mediating role of depression between ACEs and SCD. Adjusted analyses controlled for sociodemographic confounders. ACEs were positively associated with depression (B = 0.129, p …

Leveraging Data Science For Resilience: Improving Trauma-Informed Care Practice For Adverse Childhood Experience With Ai & Data Science Application, Mohmmad Arif Shaik

Master's Theses

Adverse Childhood Experiences (ACEs) have long-lasting effects on physical health, mental well-being, education, and socioeconomic outcomes. Resilient Georgia (RG), a statewide initiative, seeks to address ACEs through trauma-informed care and data-driven strategies. However, challenges in data collection, analysis, and tracking set back the effectiveness of these efforts. This study explores the role of data science and interactive visualization tools in improving outcomes for individuals and communities affected by ACEs. A key focus of this research is the development of a data science management application designed to enhance data collection and improve real-time decision-making. The application features interactive dashboards that allow …

The Importance Of Atomic Charges For Predicting Site-Selective Ir-, Ru-, And Rh-Catalyzed C-H Borylations, Shannon M. Stephens, Kyle M. Lambert

Chemistry & Biochemistry Faculty Publications

A supervised machine learning model has been developed that allows for the prediction of site selectivity in late-stage C-H borylations. Model development was accomplished using literature data for the site-selective (≥95%) C-H borylation of 189 unique arene, heteroarene, and aliphatic substrates that feature a total of 971 possible sp² or sp³ C-H borylation sites. The reported experimental data was supplemented with additional chemoinformatic descriptors, computed atomic charges at the C-H borylation sites, and data from parameterization of catalytically active tris-boryl complexes resulting from the combination of seven different Ir-, Ru-, and Rh-based precatalysts with eight different ligands. Of the over …

Challenges Associated With Pfas Detection Method In Africa, Abdullahi Tunde Aborode, Ridwan Olamilekan Adesola, Ibrahim Idris, Waheed Sakariyau Adio, Segun Olapade, Gladys Oluwafisayo, Israel Ayobami Onifade, Sodiq Fakorede, Taiwo Bakare-Abidola, Jelil Olaoye, Adedeji Daniel Ogunyemi, Oluwaseun Adeolu Ogundijo, Olamilekan Gabriel Banwo, Adetolase Azizat Bakre, Peter Oladoye, Grace Adegoye, Noimat Abeni Jinadu

Chemistry & Biochemistry Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) are a group of man-made chemicals that are widely present in many industries. Monitoring and analyzing PFAS in Africa is challenging due to the limited availability of mass spectrometry (MS), which is an essential technique for detecting PFAS. This review assesses the scope and impact of the shortage of mass spectrometry instruments in Africa, emphasizing the resulting limitations in monitoring environmental and public health threats. The review analyzes the existing PFAS monitoring, the accessibility of MS instruments, and the technical capabilities within the continent. This study suggests that fewer African countries have sufficient MS instruments, …

Nucleotide-Derived Bacterial Alarmones Attenuate The Induction Of Type-I Interferon Responses In A Murine Macrophage Reporter Cell Line, Ryan P. Kilduff, Erin B. Purcell, Lisa M. Shollenberger

Chemistry & Biochemistry Faculty Publications

The stringent response is a well-studied phenomenon in many bacterial systems and regulates resource-consuming activities such as transcription, translation, and replication. The stringent response is a well-conserved signaling framework, as are the nucleotide-derived signaling mediators, collectively referred to as (p)ppGpp or as alarmones. There is a wealth of research evaluating nucleotide-derived alarmone signaling in bacterial models, however, their potential to modulate innate immune signaling has not yet been evaluated. Several common pathogen-synthesized molecules, such as lipopolysaccharide (LPS) and cyclic-di-AMP (c-di-AMP), act as pathogen-associated molecular patterns (PAMPs), which are common patterns that alert the innate immune system of bacterial infection. The …

Modified N-Heterocyclic Carbene Catalysts For Polyurethane Synthesis, Charise D. Young

Pomona Senior Theses

Polyurethanes are widely used polymers synthesized from diisocyanate and diol molecules. They are ubiquitous polymeric materials with important industrial applications. Their increasing market value prompts the need for selective and efficient production which can be achieved through N-Heterocyclic carbene (NHC) catalysis. N-heterocyclic carbenes are heterocyclic molecules containing a carbene atom and at least one nitrogen adjacent to the carbene center. The nitrogen substituents on the adjacent nitrogen play an important role in influencing their steric and electronic properties and resultant reactivity.^1,2 There is a lack of a comprehensive understanding of the steric and electronic properties of NHCs and how …

Swimming In Sh*T: Quantifying Lagoon Flushing Impacts On Fecal Indicator Bacteria In Surf Zones Of Three Beaches On The East End Of Long Island, Ny, Brody C. Eggert

Pomona Senior Theses

This thesis investigates how lagoon flushing influences fecal indicator bacteria (FIB) concentrations—specifically enterococcus bacteria—in the surf zones of East Hampton and Southampton, New York. Focusing on the coastal lagoons of Georgica Pond, Sagg Pond, and Mecox Bay, the study analyzes how episodic inlet openings and environmental conditions affect enterococcus levels at adjacent recreational beaches. Using over 700 observations from the Surfrider Foundation’s Blue Water Task Force (BWTF) database, I construct a series of statistical models ranging from ordinary least squares to mixed effects frameworks; this thesis shows my process in developing this model. My analysis reveals that open inlets between …

Rwanda's Natural Remedies: A Fresh Look At The Fight Against Malaria, Leandre Nsabimana Ndisanze

Pomona Senior Theses

Malaria remains one of the most devastating parasitic diseases globally, disproportionately affecting sub-Saharan Africa, where Rwanda continues to face high transmission rates and rising resistance to conventional interventions. Despite decades of control efforts, the emergence of drug-resistant Plasmodium falciparum and insecticide-resistant Anopheles mosquitoes threatens to reverse recent gains. This research responds to the urgent need for sustainable and culturally relevant alternatives by exploring the therapeutic potential of Rwandan traditional medicinal plants. These indigenous remedies, long used by local healers, offer an underexplored reservoir of bioactive compounds that may provide the basis for novel antimalarial drugs.

The central hypothesis of this …

Amorphous Quininium Aspirinate From Neat Mechanochemistry: Diffracting Nanocrystalline Domains And Quick Recrystallization Upon Exposure To Solvent Vapours, Silvina Pagola, James Howard, Johannes Merkelbach, Danny Stam

Chemistry & Biochemistry Faculty Publications

Quininium aspirinate is mechanochemically prepared as a crystalline solid by liquid-assisted grinding, or as an amorphous phase (as determined by X-ray powder diffraction), by neat grinding or neat ball milling. Our previous work demonstrated using FT-IR spectroscopy that a mechanochemical reaction had occurred in the mechanically treated neat mixtures. Herein is reported that microcrystal electron diffraction (microED) afforded the discovery of two diffracting micron-size particles in the amorphous powder synthesized by manual grinding, among a majority of non-diffracting particles. Remarkably, microED data of one of them led to the known lattice parameters of quininium aspirinate. Furthermore, this so-called 'X-ray amorphous' …

A Comparison Of Microcrystal Electron Diffraction And X-Ray Powder Diffraction For The Structural Analysis Of Metal-Organic Frameworks, Erik Biehler, Silvana Pagola, Daniel Stam, Johannes Merkelbach, Christian Jandl, Tarek M. Abdel-Fattah

Chemistry & Biochemistry Faculty Publications

This study successfully implemented microcrystal electron diffraction (microED) and X-ray powder diffraction (XRPD) for the crystal structure determination of a new phase, TAF-CNU-1, Ni(C₈H₄O₄)·3H₂O, solved by microED from single microcrystals in the powder and refined at the kinematic and dynamic electron diffraction theory levels. This nickel metal–organic framework (MOF), together with its cobalt and manganese analogues with formula M (C₈H₄O₄)·2H₂O with M = Mn ^II or Co^II, were synthesized in aqueous media as one-pot preparations from the corresponding hydrated metal chlorides and sodium terephthalate, as a promising `green' synthetic route to moisture-stable MOFs. The crystal structures of the …

Protonic Capacitor Cell Energetics: Transmembrane-Electrostatically Localized Protons/Cations, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

The transmembrane-electrostatically localized protons/cations charges (TELPs/TELCs) theory can serve as a theoretical framework to better explain cell electrophysiology and elucidate bioenergetic systems including both delocalized and localized protonic coupling. According to the TELCs model, the excess positive charges of TELCs at one side of the membrane are balanced by the excess negative charges of transmembrane-electrostatically localized hydroxides anions (TELAs) at the other side of the membrane. Through the TELCs-membrane-TELAs capacitor model, the energetics of oxidative phosphorylation have recently been better elucidated in mitochondria and alkalophilic bacteria, leading to the identification of a novel Type-B energetic process. Both the TELCs model …

Deciphering The Chemistry Of Condensed Aromatic "Black" Carbon And Nitrogen In Amazonian Anthrosols, João Vitor Dos Santos, Aleksandar I. Goranov, Laís G. Fregolente, Marcia C. Bisinoti, Zhenhuan Sun, Klaus Schmidt-Rohr, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

Amazonian anthrosols are renowned for their high fertility and dark color, properties primarily attributed to the abundance of condensed aromatic carbon (ConAC) in the soil organic matter. ConAC, commonly referred to as black carbon, play a key role in the stability and nutrient retention of these soils. However, the processes governing the formation of ConAC and its transformation into oxygenated derivatives remain poorly understood. In this study, we used multiple analytical platforms to investigate the chemistry of ConAC-rich humic acids (HA) extracted from Terra Mulata de Indio, a type of Amazonian anthrosol. The results reveal that ConAC are predominantly …

Application Of Telc Model To Better Elucidate Neural Stimulation By Touch, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

Aim: This study is to better understand how the transient ion transport activity of touch receptors could change the graded potential to stimulate an action potential firing.

Methods: The latest transmembrane-electrostatically localized protons/cations charges (TELC) theory is employed for numerical analysis to calculate the neural touch signal transduction responding time required to fire an action potential spike.

Results: A neural action potential spike was constructed successfully using newly developed time-dependent TELC-based neural transmembrane potential integral equations (Equations 5, 6, and 7). The results explicated that the TELC curve has an inverse relationship with neural transmembrane potential since its curve appears …

Scientific Writing: A Guide From Data To Draft, Kristin M. Klucevsek

Open Education Materials

Textbook for ENGL302W (Scientific Writing)

CC BY-NC-SA (2025)

Using Virtual Reality To Assist Students At Academic Risk In Human Anatomy, Michael Foley, Lauren T. Lilley, Lindsay Meyers, Robert Armstrong, Lisa Fore-Arcand, Kelly Mccoy, Chad Eitel, Tod R. Clapp, Natascha Heise

Department of Pathology & Anatomy Faculty Publications

Learning human anatomy presents a significant challenge for health profession students due to the difficulty in visualizing structures in three dimensions. Virtual reality (VR) has been reported to aid in understanding these relationships. In this study, students at academic risk attended VR sessions alongside their gross anatomy course. Data from post-surveys, observations, and examinations indicated VR participants performed similarly to peers, except in head/neck and pelvis/lower limb exams where performance was lower. Students valued VR for enhancing confidence and understanding. VR shows promise in supplementing anatomy education, particularly for less complex regions, and bridging gaps in traditional learning methods.

Understanding The Impact Of The Medicaid Expansion On Hospital Length Of Stay And Emergency Department Use In Kentucky, Cameron Bushling

Theses and Dissertations--Epidemiology and Biostatistics

Three related analyses were performed to try to understand the immediate effects of Medicaid expansion on hospital systems in Kentucky. Medicaid expansion led to a large, sudden increase in the number of individuals eligible for various health care needs. This sudden increase in demand for health services lead to initial hypotheses regarding hospitals’ ability to handle this demand. The first analysis examined hospital average length of stay (LOS) using a linear mixed-effects model. Length of stay was modeled longitudinally between 2013 and 2015 to determine if significant changes in the slope of LOS could be detected after expansion (2014). Separate …

Changes In Cancer Diagnosis And Survival In The United States During The Covid-19 Pandemic, Justin T. Burus

Theses and Dissertations--Epidemiology and Biostatistics

The COVID-19 Pandemic led to global societal disruptions as political leaders and public health authorities attempted to control the spread of the newly discovered SARS- CoV-2 virus. While these measures were designed to lessen morbidity and mortality from a novel pathogen, their impact was also felt in many other, often unintended ways. The purpose of this dissertation is to use cancer surveillance research methods to examine the association between COVID-19 Pandemic-related disruptions and changes in the normal diagnosis and care of cancer in the United States.

The first two studies of this dissertation analyzed reductions in cancer diagnoses in the …

Enhancing Public Health Surveillance: Development And Validation Of Machine Learning Models For Suspected Opioid Overdose Detection In Emergency Medical Services Data, Peter J. Rock

Theses and Dissertations--Clinical and Translational Science

The ongoing opioid overdose crisis in the United States requires timely and accurate surveillance systems to inform public health responses. Traditional public health surveillance methods rely on hospital discharge data and death certificates, which suffer from significant reporting delays and miss cases where patients refuse hospital transportation. Emergency Medical Services (EMS) data presents a promising alternative with advantages in timeliness and case ascertainment but lacks validated definitions for suspected opioid overdose (SOO).

This dissertation addresses this critical gap through the development, validation, and fairness assessment of machine learning models with natural language processing (ML-NLP) for identifying SOOs in EMS data. …

Revascularization Strategies For Multivessel Disease In Acute Coronary Syndrome: Network Meta-Analysis, Khaled M. Harmouch, Mohammad Hamza, Nomesh Kumar, Zarghoona Wajid, Neel Patel, Masooma Naseem, Jawad Basit, Prakash Upreti, Manoj Kumar, Waqas Ullah, Yasar Sattar, Timir K. Paul, Emmanouil Brilakis, M. Chadi Alraies

Abington Jefferson Health Papers

BACKGROUND: The optimal revascularization strategy for patients with acute coronary syndrome (ACS) and multivessel disease (MVD) remains debated. This study compares the efficacy and safety of different revascularization strategies in these patients.

METHODS: We included 20 studies comparing staged, complete, and culprit-only (CO) revascularization strategies in patients with ACS and MVD. We divided the revascularization strategies into 3 distinct strategies: CO, complete index procedure (CIP), and complete staged procedure (CSP). We then compared CIP and CSP with CO. Outcomes studied are all-cause mortality, cardiac death, recurrent myocardial infarction (MI), need for revascularization, bleeding, contrast-induced nephropathy (CIN), stroke, bleeding, and stent …

Enhancing Faculty Self-Efficacy In Student Retention Through Teas Reading Comprehension Score Education, Katina A. Ennis

Doctor of Nursing Practice Projects

Student retention remains a persistent challenge for Associate Degree in Nursing (ADN) programs, with significant implications for the nursing workforce amid a national shortage. Faculty self-efficacy in interpreting and utilizing academic readiness data, particularly ATI TEAS reading comprehension scores, is often limited, leading to missed opportunities for early intervention. This Doctor of Nursing Practice (DNP) quality improvement project evaluated whether a targeted educational intervention could enhance faculty self-efficacy in using TEAS reading comprehension scores to support at-risk students and improve retention strategies.

The project employed a quantitative pre- and post-intervention design using the validated Teacher’s Sense of Efficacy Scale (TSES) …

Detecting Sars-Cov-2 In Ct Scans Using Vision Transformer And Graph Neural Network, Kamorudeen Amuda, Almustapha Wakili, Tomilade Amoo, Lukman Agbetu, Qianlong Wang, Jinjuan Feng

Electrical & Computer Engineering Faculty Publications

The COVID-19 pandemic has presented significant challenges to global healthcare, bringing out the urgent need for reliable diagnostic tools. Computed Tomography (CT) scans have proven instrumental in detecting COVID-19-induced lung abnormalities. This study introduces Convolutional Neural Network, Graph Neural Network, and Vision Transformer (ViTGNN), an advanced hybrid model designed to enhance SARS-CoV-2 detection by combining Graph Neural Networks (GNNs) for feature extraction with Vision Transformers (ViTs) for classification. Using the strength of CNN and GNN to capture complex relational structures and the ViT capacity to classify global contexts, ViTGNN achieves a comprehensive representation of CT scan data. The model was …

Problem-Based Learning And Artificial Intelligence, Varna Taranikanti, Srineil Vuthaluru

Books and Book Chapters

In the current digital era, significant advancements in Artificial Intelligence (AI) have influenced various fields worldwide, particularly within the health professional education sector. This progress has also percolated into the medical education system, where Problem-Based Learning (PBL) is routinely used as a key pedagogical strategy. In PBL, students are able to fully exert their exploratory skills by solve problems through a student-centered learning approach. PBL also fosters critical thinking and encourages self-directed learning through the inquiry of clinical case scenarios. This chapter investigates the integration of AI, specifically tools like ChatGPT, into PBL frameworks to enhance learning outcomes for medical …

A Spine-Specific Lexicon For The Sentiment Analysis Of Interviews With Adult Spinal Deformity Patients Correlate With Sf-36, Sf-36, And Odi Scores: A Pilot Study Of 25 Patients, Ross Gore, Michael M. Safaee, Christopher J. Lynch, Christopher P. Ames

VMASC Publications

Classic health-related quality of life (HRQOL) metrics are cumbersome, time-intensive, and subject to biases based on the patient’s native language, educational level, and cultural values. Natural language processing (NLP) converts text into quantitative metrics. Sentiment analysis enables subject matter experts to construct domain-specific lexicons that assign a value of either negative (−1) or positive (1) to certain words. The growth of telehealth provides opportunities to apply sentiment analysis to transcripts of adult spinal deformity patients’ visits to derive a novel and less biased HRQOL metric. In this study, we demonstrate the feasibility of constructing a spine-specific lexicon for sentiment analysis …

Preferences And Feasibility Of Long-Acting Technologies For The Treatment Of Hepatitis C Virus: A Survey Of Patients In Diverse Low- And Middle-Income Countries, Renae Furl, Kimberly Scarsi, Harlan Sayles, Matt Anderson, Joelle Dountio Ofimboudem, Ethel D. Weld, Imam Waked, Asmaa Gomaa, Alzhraa Al-Khatib, Fatma Mohammed Elshobary, Hailemichael Desalegn, Henok Fisseha, Sunil Solomon, Shruti Mehta, Andrew Owen, Steve Rannard, David L. Thomas, Susan Swindells

Journal Articles: Infectious Diseases

Despite available curative treatments, global rates of hepatitis C virus (HCV) infection persist with significant burden in low- and middle-income countries (LMICs). Long-acting (LA) antiviral products are in development. This study explored the challenges and opportunities in LA-HCV treatment across three LMICs: Egypt, Ethiopia and India. The survey focused on understanding barriers and facilitators to treatment, with emphasis on LA treatment preferences. Four-hundred respondents completed a survey including demographics, HCV treatment history and preferences for injections, implants and microarray patches (MAPs) compared to pills. Overall, 78% of respondents were willing to receive injections, 43% were willing to receive implants and …

A Happy Medium?: Using Image Generators To Explore Solution-Focused Art Therapy’S Miracle Question, Daniel A. Hernried

Art Therapy | Master's Theses

This mixed methods, randomized, single-session study tested whether integrating text-to-image generations into Solution-Focused Brief Art Therapy alters therapeutic rapport and short-term outcomes relative to traditional artmaking materials. Participants were assigned by coin flip to create using either a text-to-image generator or convention media (23 per group), completing immediate and three-day follow-ups. Alliance was measured using DREAM (Dimensions of Regard, Empathy, and Authenticity Metric), and problems were rated pre/post; groups did not differ significantly on DREAM total or facets, and both modalities produced reliable pre-to-post reductions in problem severity. At the same time, process differences were pronounced: the AI condition showed …