Digital Commons Network^™

A Framework For Mixed Reality Within Healthcare Education, Benyamin Ebadinia

Theses

Understanding complex three-dimensional systems and spatial relationships is a recurring difficulty in healthcare education, where students are often expected to reason about internal structures and multi-system processes from 2D diagrams, textbook figures, and static mannequins. This thesis presents the design, implementation, and mixed-methods evaluation of Systems Simulation, a reusable mixed reality (MR) application intended to help undergraduate nursing students explore human anatomy and pathophysiology using immersive 3D visualization.

Built in C# with the StereoKit framework for Microsoft HoloLens 2, Systems Simulation organizes nine anatomical body systems within a shared application. Learners can select a system, anchor the model in their …

Enhancing Engagement: Integrating Sensory-Based Strategies For Students With Emotional Behavior Disorders In Genereal Education Classrooms, Hailey Boline

Occupational Therapy Capstones

Purpose: This scholarly project aims to develop and implement a toolkit designed to support teachers and paraprofessionals in managing the sensory, behavioral, and educational needs of students with Emotional Behavioral Disorders (EBD) and those who have experienced childhood trauma in general education classrooms. By integrating occupational therapy techniques and sensory-based interventions into classroom settings, this project seeks to enhance students' ability to self-regulate, ultimately improving academic engagement and social participation.

Methods: A multi-phase approach guided by the Ecology of Human Performance Model (EHP), beginning with a comprehensive literature review to identify best practices in sensory-based interventions for students with EBD …

Ot Role In Staff Development In Schools To Promote Continuation Of Care, Elise Gapp

Occupational Therapy Capstones

Background: School-based occupational therapy practitioners assume various collaborative roles to improve student performance, promote the carryover of student progress, and enhance teacher satisfaction (Frolek Clark & Hollenbeck, 2019; Shepherd et al., 2019). School-based occupational therapy practitioners experience many barriers to collaborative practice, which limits the carryover of interventions and strategies that support students (Benson et al., 2019; Edick et al., 2023; Jeremy et al., 2024; Mowell et al., 2023).

Purpose: The purpose of this project was to create a product for school-based occupational therapy practitioners and school support staff to use in collaboration to promote carryover of interventions and strategies …

Benefits Of Nature-Based Play For Children: An Educational Resource For Parents, Kaitlyn Peterson

Occupational Therapy Capstones

Background: In recent years, children’s use of technology has increased, decreasing the time they spend playing in natural contexts and time spent building the parent-child relationship. The lack of time spent in outdoor contexts has negative influences on the child’s overall health and well-being. The time a child spends with their parent is vitally important for a child’s development, view of the world, and sense of belonging. Parents assist children throughout development by supporting their understanding of themselves and the world, along with supporting the child’s ability to communicate with their parents. Interactions with technology, particularly overuse, can influence a …

Development Of Cerium Oxide Based Polymer Composites With Enhanced Cytocompatability For Biomedical Applications, Roshna Cherugail

Honors Undergraduate Theses

This thesis presents the synthesis and characterization of cerium oxide nanoparticles (CNPs), and silver-doped cerium oxide nanoparticles (AgCNPs) loaded in alginate beads that were designed to be applied in biomedical settings. Cerium oxide was chosen for its antioxidant and anti-inflammatory capabilities, and silver oxide was selected to enhance antimicrobial functionality, both of which are pivotal in expedited wound closure and promoting cellular proliferation. Through the use of an advance electrospray encapsulation apparatus, alginate-based polymer beads were created by incorporating either CNPs or AgCNPs into the matrix. These beads were later characterized using a range of microscopic and FTIR analyses, in …

Effects Of Round-Up On The Environment, Sandra J. Marcu

Journal of Earth and Life Science

Many people around the world have used and still currently use Roundup but are unaware of the effects it has on the environment. Roundup is a spray on application weedkiller that is widely used around the world today both residentially and commercially. It enables its user to grow a garden or a field of crops with a no-tilling approach to eliminate weeds. It is a well-known and popular choice for killing weeds that has been around since the mid 1970’s (Oca, 2017). John Franz, a Monsanto scientist discovered that glyphosate (main ingredient in Roundup) was an herbicide or weedkiller, and …

Human Serum Albumin Interaction With Organochlorine Pesticides, D. S. Sanford, R. Yadav, A. Mishra

Journal of the Arkansas Academy of Science

Human serum albumin (HSA) is the most abundant blood plasma protein and plays a crucial role in drug transport and physiological homeostasis. HSA has a highly flexible structure consisting of three domains, each with multiple binding sites lined with hydrophobic and hydrophilic residues. The structural properties of HSA make it a robust reservoir and receptor for various endogenous and exogenous compounds, including therapeutic drugs. Organochlorine pesticides (OCPs) are a subclass of pesticides characterized by their chlorine content. Once widely used, these compounds remain persistent in the environment and biological systems despite regulatory restrictions in many developed countries. The strong ligand-binding …

Comparison Of Machine Learning Models For Colon Cancer Survival: Predictive Modeling Approach, Reuben Adatorwovor, Motolani E. Ogunsanya, Bin Huang, Richard Charnigo, Olufunmilola Abraham

Biostatistics Faculty Publications

Background: Colon cancer is a leading cause of cancer-related deaths worldwide, with survival influenced by risk factors, treatment type, and patient characteristics. Traditional statistical models, such as Kaplan-Meier curves, have been widely used to estimate survival probabilities. However, these models often have difficulty handling complex interactions, covariates, and nonlinear relationships between risk factors. Recently, machine learning (ML) techniques have emerged as promising tools for improving survival prediction by handling large covariates and capturing complex patterns.

Objective: This study compares several ML models to accurately estimate colon cancer survival by leveraging data from the Kentucky Cancer Registry. By identifying key risk …

Match Accuracy Of Burned Teeth: A Pilot Study Of Allied Dental Professionals, Brenda T. Bradshaw, Marsha A. Voelker, Samantha C. Vest, Sinjini Sikdar

Dental Hygiene Faculty Publications

Purpose: The purpose of this pilot study was to assess allied dental professionals' match accuracy of burned teeth; a skill required by disaster victim identification (DVI) team members.

Methods: This cross-sectional study used a convenience sample of registered dental hygienists (RDH) (n=15) and dental assistants (DA) (n=15) to assess their match accuracy of burned teeth with simulated antemortem (AM) and postmortem (PM) images. Fifteen human teeth were heated at 400°C for 15 minutes. Prior to and following heat alteration, each tooth was photographed and radiographed. Images were presented to participants in randomized order, and they were instructed to correctly match …

Improving Dental Hygiene Students' Knowledge, Attitudes, And Confidence Toward Prenatal Oral Health Through Experiential Learning, Denise C. Mckinney, Sinjini Sikdar, Shillpa Naavaal

Dental Hygiene Faculty Publications

Purpose Maintaining optimal oral health is essential for maternal health as well as the health of their child. The purpose of this pilot study was to examine dental hygiene (DH) students' knowledge of prenatal oral health before and after receiving an asynchronous prenatal oral health care training (POHCT), and their attitudes and self-perceived confidence before and after receiving an experiential learning opportunity with a pregnant and/or post-partum client at a Women's Infants and Children nutrition program (WIC) clinic.

Methods A one-group pre/post-test design was used. This IRB-approved study (#2027439-4) utilized a convenience sample of DH student participants (n=37) in their …

Machine Learning Applications In Epigenomics And Its Association With Health And Disease, Trevor Doherty

Doctoral

Epigenetic modifications can lead to altered phenotypes without a change in the DNA sequence itself. Disrupted gene expression regulated by epigenetic processes can result in cancers, autoimmune diseases and various other maladies. Machine learning (ML) involves the use of algorithms and models which are trained to learn patterns in data, and has demonstrated remarkable success in solving diverse, complex challenges. Epigenomic studies, such as those that use DNA methylation (DNAm) data, increasingly make use of ML techniques to process extremely high dimensional data obtained from high throughput platforms e.g., DNAm arrays. These datasets suffer from the curse of dimensionality, increased …

Clinician Perspectives On Virtual Reality Use In Physical Therapy Practice In The United States, Danielle T. Felsberg, Jared T. Mcguirt, Scott E. Ross, Louisa D. Raisbeck, Charlend K. Howard, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

The primary goal of physical rehabilitation is to assess movement impairments and restore function to improve overall quality of life. Virtual reality (VR) may provide the optimal environment to promote these goals due to its motivating and modifiable nature which can be difficult to accomplish through traditional real-world therapeutic methods. Current research of VR for rehabilitation has demonstrated that VR interventions can produce clinically meaningful change in motor outcomes. Despite this, adoption and usage of VR by physical therapy professionals is unclear due to the limited research in this area. Thus, the purpose of this study was to identify the …

Clear Speech Intervention In Parkinson’S Disease: A Single Case Design Examining Acoustic And Aerodynamic Outcomes Following A Structured Protocol, Zachariah Jordan Backus

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Clear Speech Intervention in Parkinson’s Disease: A Single Case Design Examining Acoustic and Aerodynamic Outcomes Following a Structured Protocol

Zachariah Backus

Purpose:

Parkinson Disease (PD) is a neuro-progressive movement disorder that impacts all movement of the body, including speech production. Ninety percent of individuals living with PD will experience hypokinetic dysarthria, a motor speech disorder, during the progression of their disease. Clear speech instruction is a treatment strategy used to increase motor speech outcomes in those with PD. Studies have shown positive changes in articulation, prosody, voice, and listener perception measures in those with PD after clear speech instruction …

On The Frontline: Stop The Bleed© Training For School Staff, Mary Michaela Hinson

Doctor of Nursing Practice Projects

The American College of Surgeons’ Stop the Bleed© course was introduced in 2015 following an outcry from the community surrounding the Sandy Hook Elementary School shooting. The Stop the Bleed© course was developed as a tool for training that any person could participate in, despite their medical background or knowledge. The course is comprised of a 30-minute didactic portion followed by a 30-minute hands-on portion where participants can practice applying tourniquets, packing a wound, and applying manual pressure. This DNP project aimed to educate school staff in a high school located in North Carolina on Stop the Bleed© in an …

Skinrisk Ai, Spencer Simms

Williams Honors College, Honors Research Projects

SkinRisk AI is an exploration of the opportunities for implementing machine learning (ML) and artificial intelligence (AI) in the medical technology field, specifically in the early detection of skin cancer. This project presents the design, development, and evaluation of a mobile application that allows users to capture images of skin lesions and receive a machine learning assisted risk assessment. The system combines a convolutional neural network (CNN) for image analysis with an intuitive mobile app built using Flutter, FastAPI, and Supabase to deliver real time screening.

Motivated by the rising skin cancer rates and importance of early detection, SkinRisk AI …

Interaction Of Cardiac Leiomodin With The Native Cardiac Thin Filament, Madison Little, Cristina M. Risi, Tania M. Larrinaga, Mason D. Summers, Tyler Nguyen, Garry E. Smith Jr., Jennifer Atherton, Carol C. Gregorio, Alla S. Kostyukova, Vitold E. Galkin

Department of Biomedical and Translational Sciences Faculty Publications

Every heartbeat depends on cyclical contraction-relaxation produced by the interactions between myosin-containing thick and actin-based thin filaments (TFs) arranged into a crystalline-like lattice in the cardiac sarcomere. Therefore, the maintenance of thin filament length is crucial for myocardium function. The thin filament is comprised of an actin backbone, the regulatory troponin complex and tropomyosin that controls interactions between thick and thin filaments. Thin filament length is controlled by the tropomodulin family of proteins; tropomodulin caps pointed ends of thin filaments, and leiomodin (Lmod) promotes elongation of thin filaments by a “leaky-cap” mechanism. The broader distribution of Lmod on the thin …

Organization And Activation Of Caffeine Expectancies, Catherine S. Forsyth

Honors Undergraduate Theses

Caffeine is the most consumed and widely used psychoactive substance in the world. Whether someone uses caffeine or not, expectations about use can be influential to some degree. Expectancies exist everywhere and are extremely influential in all aspects of life. Regarding drug use, expectancies can affect behavior, outcomes, and one’s experience with the drug. Caffeine is no exception, caffeine expectancies have been seen to play a role in several actions such as the development, maintenance, and reinforcement of caffeine use. This study examined latent use profiles of caffeine and relationships between the profiles and the activation of caffeine expectancies. Multidimensional …

Proteomics Profiling Of Research Models For Studying Pancreatic Ductal Adenocarcinoma, Mathilde Resell, Hanne-Line Rabben, Animesh Sharma, Lars Hagen, Linh Hoang, Nan T. Skogaker, Anne Aarvik, Eirik Knudsen Bjåstad, Magnus K. Svensson, Manoj Amrutkar, Caroline S. Verbeke, Surinder K. Batra, Gunnar Qvigstad, Timothy C. Wang, Anil Rustgi, Duan Chen, Chun-Mei Zhao

Journal Articles: Biochemistry & Molecular Biology

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival rate of 10-15% due to late-stage diagnosis and limited efficacy of existing treatments. This study utilized proteomics-based systems modelling to generate multimodal datasets from various research models, including PDAC cells, spheroids, organoids, and tissues derived from murine and human samples. Identical mass spectrometry-based proteomics was applied across the different models. The preparation and validation of the research models and the proteomics were described in detail. The assembly datasets we present here contribute to the data collection on PDAC, which will be useful for systems modelling, …

Enhancing Channel Data Savings And Information Transfer Efficiency In Ultrasound Imaging, Sai Konda, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Ultrasound is a popular imaging technique mainly due to its non-invasive nature. And so, it is being used in a variety of applications. Due to plane wave imaging technique in ultrasound, frame rate of ultrasound imaging has the potential for being very high. Due to which, many channel data frames are being generated within a few seconds. As a result, tasks such as storing data frames and transferring them from front end ultrasonic system to processing computers are presenting significant challenges. Our current research work minimized these issues. We proposed and implemented: (a) Data encoding technique - We combined every …

The Pre-Polarization And Concentration Of Cells Near Micro-Electrodes Using Ac Electric Fields Enhances The Electrical Cell Lysis In A Sessile Drop, Kishor Kaphle, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell lysis is the starting step of many biomedical assays. Electric field-based cell lysis is widely used in many applications, including point-of-care (POC) applications, because it provides an easy one-step solution. Many electric field-based lysis methods utilize micro-electrodes to apply short electric pulses across cells. Unfortunately, these cell lysis devices produce relatively low cell lysis efficiency as electric fields do not reach a significant portion of cells in the sample. Additionally, the utility of syringe pumps for flow cells in and out of the microfluidics channel causes cell loss and low throughput cell lysis. To address these critical issues, we …

Key Brain Region Identification In Obesity Prediction With Structural Mri And Probabilistic Uncertainty Aware Model, Walia Farzana, Megan A. Witherow, Ahmed Temtam, Liangsuo Ma, Melanie Bean, F. Gerry Moeller, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: Predictive performance alone may not determine a model’s clinical utility. Neurobiological changes in obesity alter brain structures, but traditional voxel-based morphometry is limited to group-level analysis. We propose a probabilistic model with uncertainty heatmaps to improve interpretability and personalized prediction. Methods/Study Population: The data for this study are sourced from the Human Connectome Project (HCP), with approval from the Washington University in St. Louis Institutional Review Board. We preprocessed raw T1-weighted structural MRI scans from 525 patients using an automated pipeline. The dataset is divided into training (357 cases), calibration (63 cases), and testing (105 cases). Our probabilistic model …

A Fast Framework For Generating Radioactive Mixture Spectra And Its Application To Remote High-Performance Mixture Identification, Chiman Kwan, Bulent Ayhan, Adam Stavola, Kazi Aminul Islam, Hongfang Zhang, Jiang Li

Electrical & Computer Engineering Faculty Publications

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework.

Electronic Health Records In Non-Hospital Settings Of Developing Economies: A Systematic Review On Enablers And Barriers, Bejie Rodriguez, Joenelyn Kaye Demoral, Jan Jacob Carpio, Alan Napoleon Gultia, Gloria Shiela Coyoca, Cecilio Garciano, Lemuel Clark Velasco

Institute of Philippine Culture (IPC)

In recent years, rapid advancements in Information and Communications Technology (ICT) have greatly transformed the healthcare landscape by streamlining health data management and providing decision-makers with secure and convenient access to health records. In developing economies, limited resources hinder healthcare access. Implementing EHRs in non-hospital settings is essential for enhancing healthcare quality and accessibility. While existing literature supports EHR use, further research is needed to pinpoint specific barriers and enablers. Using PRISMA guidelines, 18 relevant articles were systematically analyzed with the Human, Organization, and Technology Fit (HOT-fit) framework to examine these factors in non-hospital settings within developing economies. This study …

A Governance-Centric Framework For Strengthening Healthcare Cybersecurity: A Systems Perspective, Sujatha Alla, Sai Gireesh Komaragiri, Teresa Duvall, Satluk Karahan, Nagesh Bheesetty, Vijay Kumar Chattu

Engineering Management & Systems Engineering Faculty Publications

Healthcare systems face unprecedented security and privacy challenges due to increasing digitization and interconnectedness. This paper provides a comprehensive analysis of these challenges by examining various cyberattacks, defensive mechanisms, and governance frameworks within modern healthcare infrastructure. The research systematically categorizes prevalent security threats, such as ransomware, insider threats, and data breaches, identifying vulnerabilities specific to healthcare systems. Furthermore, the study evaluates current defensive strategies, including encryption techniques, access control systems, and intrusion detection tools, assessing their effectiveness against complex cyber threats. A key focus is placed on governance structures and their role in cybersecurity resilience. The research explores how regulatory …

Llm-Driven Fmea For Safe Human-Robot Collaboration In Disassembly, Morteza Jalali Alenjareghi, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn

Articles dans des actes de congrès

Disassembly operations often present unstructured and unpredictable scenarios, such as handling hazardous materials, addressing ergonomic strain, and managing dynamic robot interactions that pose safety risks. To tackle these challenges, we propose an innovative use of large language models (LLMs) to enhance failure mode and effect analysis (FMEA) in the context of human-robot collaboration (HRC) for disassembly tasks. We developed an LLM system leveraging retrieval-augmented generation (RAG) for real-time risk analysis and recommendation generation. RAG retrieves domain-specific information from the FMEA knowledge database, enabling accurate risk analysis, contextual understanding, and relevant recommendations based on user input and operational data. Evaluation of …

Comparative Efficacy Of Hallucinogens In Treating Mood Disorders Through A Meta-Analysis Of Symptom Reduction, Dosage, And Duration, John Marco D.F. Muniz

Honors Undergraduate Theses

Background: Hallucinogens including psilocybin, lysergic acid diethylamide (LSD), ketamine, N,N-dimethyltryptamine (DMT) (as ayahuasca), have re-emerged as potential rapid-acting treatments for mood disorders. We conducted a meta-analysis of placebo-controlled trials evaluating their efficacy in depression and anxiety disorders. Methods: A systematic review identified 12 trials (Total ≈ 670) meeting inclusion criteria (randomized, placebo-controlled). Data on Cohen’s d and Hedges’ g effect sizes for depression- and anxiety-related outcomes were extracted. We computed pooled effect sizes (weighted by sample size and inverse variance), performed subgroup analyses by drug, diagnosis, follow-up duration, and outcome measure type, and assessed heterogeneity (I², Q …

Three-Dimensional Analysis Of Dental Arch Form In Relation To The Vertical Facial Pattern In Class I Patients: A Cross-Sectional Study, Ahmad Ghassan Droubi, Islam Gad, Aly Osman

International Arab Journal of Dentistry

Introduction: Understanding the relationship between dental arch form and vertical facial pattern is crucial in orthodontic diagnosis and treatment planning. Variations in vertical facial morphology can influence dental arch form, which in turn impacts the effectiveness and stability of orthodontic interventions.

Objectives: The study explores the associations between dental arch form with the different vertical facial patterns, including hyperdivergent, normodivergent, and hypodivergent patterns in skeletal Class I patients.

Methods: A cross-sectional observational design was employed to examine a sample of 48 patients with skeletal Class I seeking orthodontic treatment; of which 24 males and 24 females. Each …

Generating Real-World Evidence In Early Alzheimer's Disease: Considerations For Applying The Target Trial Emulation Framework To Study The Safety Of Anti-Amyloid Therapies, Xiaojuan Li, Sonal Singh, Bahareh Rasouli, Jennifer Lyons, Noelle M. Cocoros, Richard Platt, Ivan Abi-Elias, Jerry H. Gurwitz

Department of Medicine Faculty Publications

Anti-amyloid beta monoclonal antibodies (anti-Aβ mAbs) have received approval from the US Food and Drug Administration for the treatment of patients with mild cognitive impairment or mild dementia due to Alzheimer's disease (collectively known as early AD) based on evidence from clinical trials. However, whether findings from these trials are generalizable to the real world is uncertain. We need reliable evidence on the real-world safety of these treatments to inform decision making for clinicians, patients, and caregivers. Using lecanemab as an exemplar, we outline the key considerations in designing and implementing an observational study on safety and utilization outcomes using …

The Reliability Gap: How Traditional Search Engines Outperform Artificial Intelligence (Ai) Chatbots In Rosacea Public Health Information Quality, Houston C. Nelson, Morgan T. Beauchamp, April A. Pace

Department of Medicine Faculty Publications

Background: The internet has become a primary source of health information for the public, with important implications for patient decision-making and public health outcomes. However, the quality and readability of this content vary widely. With the rise of generative artificial intelligence (AI) tools such as ChatGPT and Gemini, new challenges and opportunities have emerged in how patients access and interpret medical information.

Objective: To evaluate and compare the quality, credibility, and readability of consumer health information provided by traditional search engines (Google, Bing) and generative AI platforms (ChatGPT, Gemini) using three validated instruments: DISCERN, JAMA Benchmark Criteria, and Flesch-Kincaid Readability …

Factors Influencing Reflection And Self-Assessment Of Simulation Performance: Comparing Student And Preceptor Ratings, Kaitlin R. Sibbald, Diane E. Mackenzie

Journal of Occupational Therapy Education

Simulation with simulated patients is increasingly used in occupational therapy. Ensuring the debrief component meets student needs to develop their self-assessment skills for participating in a self-regulating profession is essential. This explanatory mixed-methods research sought to explore factors contributing to accurate and inaccurate self-assessment of simulation performance for novice occupational therapy learners in a part-time introductory fieldwork course. Self-ratings and preceptor-ratings of performance on eleven simulation objectives were compared for sixty-five novice occupational therapy students. Factor analysis was used to explore contributors to differences in ratings between students and preceptors. Students’ written plus-delta debrief reflections were analyzed to explore what …