Other Medicine and Health Sciences Commons^™

Mathematical Modeling Of The Combined Effects Of Thermal Burn And Local Irradiation, Quintessa Hay, Rachel Jennings, Amy Creel, Kyle Gaffney, Christina Wagner, Kidist Maxwell, Ginu Unnikrishnan, Tyler Dant

Biology and Medicine Through Mathematics Conference

No abstract provided.

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 …

Evolving Solutions For Red Blood Cell Preservation, Ali Alkafaji, Charles A. Elder, Mohammad Zaidi, Kavin Parthiv, Michael A. Menze

The Cardinal Edge

In emergencies such as natural disasters, armed conflicts, or during outer space missions, the availability of transfusable blood can mean the difference between life and death. Red blood cells (RBCs) must be stored at +4 ± 2 °C and have a shelf life of just 42 days, which makes maintaining a stable blood supply during adverse conditions extraordinarily challenging. This challenge was especially apparent during the COVID-19 pandemic when hospitals faced severe blood shortages. Freeze-drying, or lyophilization, offers a promising avenue to extend the shelf life of RBCs for transfusion during crises. However, a significant hurdle in dry preservation is …

Guidelines For Standard Basic Notations In Applied Statistics, Abhaya Indrayan, Shivani Saini Ms

COBRA Preprint Series

Whereas some statistical notations are standard and uniformly used by different workers, many are not. Varying notations lead to confusion among the readers, particularly those engaged with applied statistics material, such as medical professionals. This communication proposes that all basic notations be standardized so that the same notations are consistently used by different authors, in different books, journals, and articles for the benefit of those who are not rigorously trained statisticians. Guidelines for such standard notations are also provided. The lead must be taken by statisticians.

Error-Driven Density Control For Compact Gaussian Splatting Under Sparse Supervision, Abdelrhman Elrawy

Theses and Dissertations (Comprehensive)

This thesis studies efficiency and stability challenges in Gaussian-splatting-based reconstruction under sparse supervision. In few-shot novel view synthesis, standard 3D Gaussian Splatting (3DGS) can overfit the limited training views and grow an unnecessarily large number of primitives due to limitations in its Adaptive Density Control (ADC) mechanism. This thesis introduces an error-driven reformulation of ADC that triggers densification using opacity gradients as a lightweight proxy for rendering error, and shows that such aggressive densification must be paired with delayed and conservative pruning to prevent destructive create--destroy cycles. When combined with depth-based geometric regularization, the resulting framework produces substantially more compact …

Geovig And Purevig: Geometry-Aware Architectures For Efficient Computer Vision, Omar Ismail

Theses and Dissertations (Comprehensive)

Deploying deep learning models for medical image analysis on mobile devices requires a balance between inference latency, memory footprint, and delineating anatomical boundaries with high accuracy. While Convolutional Neural Networks (CNNs) and mobile Vision Transformers (ViTs) offer efficiency, they often struggle to model the irregular, non-local geometric structures inherent in biological tissues without incurring prohibitive computational costs. In this thesis, we introduce GeoViG (Geometric Vision Graph), an architecture that bridges the gap between efficient grid-based processing and explicit Geometric Deep Learning. GeoViG introduces a novel transition from high-resolution pixel grids to low-resolution dynamic graphs via a SpreadEdgePool operator, a geometry-aware …

Enhancing Cataract Surgery Outcomes: Optimal Use Of Pre- And Post-Operative Eye Drops, Keith Skolnick M.D., Anu Valiaveedu

Mako: NSU Undergraduate Student Journal

Many preoperative and postoperative cataract patients struggle with comprehending the use of prescription medication as directed. Language barriers and low health literacy levels are major factors contributing to improper use of prescriptions. To increase patients comprehension, the Fort Lauderdale Eye Institute employed an educational intervention consisting of a live presentation and an instructional video. Results found that 44% of patients were hesitant to ask questions to clinical staff, 32% felt overwhelmed, and nearly 70% lacked confidence in using their prescribed eye drops. Following the intervention, 91% of patients reported increased confidence in their medications, and most indicated that the video …

False Narratives, Real Consequences, Russell W. Cantrell, Matt Campbell

Shelby Hall Graduate Research Forum Posters

Social media is an increasingly significant tool in modern cyber warfare, capable of rapidly shaping public opinion. The swift dissemination of information complicates efforts to distinguish fact from fiction [1]. During public health crises, healthcare professionals use these platforms to share updates, yet their credible content must contend with false or deliberately misleading narratives [2]. This environment creates an opportunity for cyberattacks through social media influence campaigns [3]. While disinformation's role in political interference has been widely studied, its potential to destabilize healthcare remains largely unexplored. Prior research primarily focuses on how vaccine misinformation affects the general public [4]. This …

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 …

Ethical Aspects Of Utilising Artificial Intelligence In Clinical Settings, Jeffrey Byrnes, Michael Robinson

Philosophy Faculty Articles and Research

In response to recent proposals to utilize artificial intelligence (AI) to automate ethics consultations in healthcare, we raise two main problems for the prospect of having healthcare professionals rely on AI-driven programs to provide ethical guidance in clinical matters. The first cause for concern is that, because these programs would effectively function like black boxes, this approach seems to preclude the kind of transparency that would allow clinical staff to explain and justify treatment decisions to patients, fellow caregivers, and those tasked with providing oversight. The other main problem is that the kind of authority that would need to be …

Characterization Of Aromatic Stationary Phases For Uses In High Performance Liquid Chromatography, Anastasia Davis

Honors Theses

High Performance Liquid Chromatography (HPLC) is an analytical chemist technique used to separate a sample into its components to characterize and study a specific molecule or compound. Traditionally, High-Performance Liquid Chromatography in different industries, such as the environmental and pharmaceutical fields, uses stationary phases that are already well characterized, such as the C18 stationary phase for separation. However, aromatic stationary phases have recently been produced, which have phenyl groups bonded to the interior surface of the column. Still, they have not been well characterized because of how modern they are. This project characterized several aromatic stationary phases (Biphenyl, pentafluorophenyl, and …

Review Of Data Bias In Healthcare Applications, Atharva Prakash Parate, Aditya Ajay Iyer, Kanav Gupta, Harsh Porwal, P. C. Kishoreraja, R. Sivakumar, Rahul Soangra

Physical Therapy Faculty Articles and Research

In the area of medical artificial intelligence (AI), data bias is a major difficulty that affects several phases of data collection, processing, and model building. The many forms of data bias that are common in AI in healthcare are thoroughly examined in this review study, encompassing biases related to socioeconomic status, race, and ethnicity as well as biases in machine learning models and datasets. We examine how data bias affects the provision of healthcare, emphasizing how it might worsen health inequalities and jeopardize the accuracy of AI-driven clinical tools. We address methods for reducing data bias in AI and focus …

Hgs-3 The Influence Of A Tandem Cycling Program In The Community On Physical And Functional Health, Therapeutic Bonds, And Quality Of Life For Individuals And Care Partners Coping With Parkinson’S Disease, Leila Djerdjour, Jennifer L. Trilk

SC Upstate Research Symposium

Purpose Statement: Several studies have shown that aerobic exercise can have a positive impact on alleviating symptoms experienced by individuals with Parkinson's disease (PD). Despite this evidence, the potential benefits of exercise for both PD patients and their care partners (PD dyad) remain unexplored. This research project investigates the effectiveness, therapeutic collaborations, and physical outcomes of a virtual reality (VR) tandem cycling program specifically designed for PD dyads.

Methods: Following approval from the Prisma Health Institutional Review Board, individuals with PD were identified and screened by clinical neurologists. The pre-testing measures for PD dyads (N=9) included emotional and cognitive status …

Outpatient Fall Prevention In Ambulatory Adults 65 Years Old And Over, Dorothy L. Osborne-White

Doctor of Nursing Practice (DNP) Scholarly Projects - Archive

Background: In the United States (U.S.), falls are the leading cause of injury among adults 65 and over, resulting in 36 million falls yearly (Moreland et al., 2020). According to the Centers for Disease Control and Prevention (CDC, 2023), one in four older adults experiences a fall each year. Falls are the world's second most prominent cause of accidental deaths (World Health Organization [WHO], 2021). Falls are the leading cause of both fatal and non-fatal injuries among older adults (Moreland et al., 2020).

Methods: A quality improvement project that included a fall bundle was implemented in a primary clinic. A …

The Oral-Microbiome-Brain Axis: A Thorough Review On The Relationship Between Periodontitis And Alzheimer’S Disease And A Proposed Innovative Application Of Biomagnetism As A Means Of Alternative Therapy., Taha Al Hassan, Noah Al-Hassan, Maria Quiñones-Peña, Juan Lopez-Alvarenga, Seratna Guadarrama-Beltran

MEDI 9331 Scholarly Activities Clinical Years

The relationship between periodontitis and Alzheimer's disease (AD) has garnered significant attention due to the potential influence of chronic oral inflammation on neurodegenerative processes. Our hypothesis is supported by the oral-microbiome-brain axis and highlights the possibility that chronic periodontitis contributes to cognitive decline by promoting systemic inflammation and neuroinflammation, mediated by specific pathogenic microorganisms within the oral microbiome. Our findings reveal a strong association between elevated levels of Porphyromonas gingivalis and Treponema denticola, red complex bacteria, and markers of systemic inflammation, such as C-reactive protein (CRP) and pro-inflammatory cytokines. Additionally studies have demonstrated that beta amyloid plaque in rat …

Machine Learning-Based Classification Of Chronic Traumatic Brain Injury Using Hybrid Diffusion Imaging, Jennifer Muller, Ruixuan Wang, Devon Middleton, Mahdi Alizadeh, Kichang Kang, Ryan Hryczyk, George Zabrecky, Chloe Hriso, Emily Navarreto, Nancy Wintering, Anthony J. Bazzan, Chengyuan Wu, Daniel A. Monti, Xun Jiao, Qianhong Wu, Andrew B. Newberg, Feroze Mohamed

Marcus Institute of Integrative Health Faculty Papers

BACKGROUND AND PURPOSE: Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging.

MATERIALS AND METHODS: A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging …

Heterochiral Dna Nanotechnology For Biomedical Applications, Tracy L. Mallette

Biomedical Engineering ETDs

In the past 30 years, there have been major advancements on how to treat and diagnose disease because of the improvement and increase in accessibility of sequencing technology. Nucleic acid-based therapeutics can manipulate protein expression. Likewise, pathogens can be identified and detected with single nucleotide specificity. However, the underlying oligonucleotide technology requires protection against natural defense systems that have evolved to destroy foreign nucleic acids. Many chemical modifications that can protect nucleotides also have significant cytotoxic side effects and must be carefully designed into the strands. A novel way to protect against nuclease-mediated degradation is through the use of mirror-image, …

Disrupting Cisheteronormativity In Stem Through Humanism, Meg C. Jones, Desiree Forsythe, Rachel Friedensen, Annemarie Vaccaro, Ryan A. Miller, Ezekiel Kimball, Rachael Forester

Biology, Chemistry, and Environmental Sciences Faculty Books and Book Chapters

Cisheteronormativity is prevalent throughout college STEM discourses and classrooms. In this paper, we present findings from a U.S. based study focused on the experiences of collegiate STEM students with minoritized identities of sexuality and gender (MIoSG) as the backdrop for discussing how current harmful ideologies in STEM perpetuate cisheteronormativity through discursive practice. We propose that humanistic classrooms and pedagogy can work to dismantle cisheteronormative D/discourses in STEM and create MIoSG inclusive STEM classrooms and programs. Our findings highlight the ways participants experienced cisheteronormative D/discourses in their collegiate STEM contexts. We discuss how these experiences might be mitigated through humanistic educational …

Hipaa Vs. Medical Research: Improving Patient Care Through Integration Of Data Privacy And Data Access, Katherine D'Ordine

Honors Projects in Data Science

The purpose of this research is to understand the current relationship between data access and data privacy in the health care industry and attempt to find a way that important health care research can still be conducted amidst HIPAA regulations. There is a lack of extensive research on the impacts of data privacy on health care research due to access regulations, so a survey was created regarding current data processes and recommendations for creating a healthier relationship between privacy and access for research. It was distributed to anyone in health care, analytics, or research to get a variety of perspectives. …

Clinical Effects Of Lactobacillus Reuteri Probiotic In The Treatment Of Chronic Periodontitis: A Systematic Review Of Randomized Controlled Trials, Josephine Ram, Shilpa Bhandi, Kamran H. Awan, Frank Licari, Shankargouda Patil

Annual Research Symposium

No abstract provided.

Investigating The Use Of Conversational Agents As Accountable Buddies To Support Health And Lifestyle Change, Ekaterina Uetova, Dympna O'Sullivan, Lucy Hederman, Robert J. Ross

Academic Posters Collection

The poster focuses on the role of conversational agents in promoting health and well-being. Results of the literature review indicate that negative emotions can hinder individuals from taking necessary actions related to their health. The study concludes that understanding and addressing emotional barriers is essential to facilitating early access to health services and improving well-being. The poster outlines plans to investigate motivation strategies, develop a prototype conversational agent based on user study insights and chat log data, and incorporate emotion regulation to effectively manage users' emotional experiences.

Thermodynamic Analysis Of Digestate Pyrolysis Coupled With Co2 Sorption, Antonella Dimotta, Cesare Freda

Conference papers

To date the management of digestate is a crucial task for anaerobic digestion process. In the present work a strategy for digestate management is thermodynamically analyzed by a commercial software for process simulation called CHEMCAD®. Pyrolysis of digestate is simulated by a minimization of the free Gibbs energy. The sequestration of the carbon dioxide (CO2) released by the pyrolysis is investigated by the addition of calcium oxide, in order to reduce CO2 emissions. The effect of the pyrolysis temperature between 400–900 °C and of the CaO/digestate mass ratio between 0–0.5 was discussed, as well. The CHEMCAD application allowed to investigate …

Changing Stem To Steam: An Analyzation On The Effects Of Art Integration Up To The University Level, Elizabeth Richmond

Honors Projects

This Honors Project is a combination of an artistic, creative project and a research driven analysis. The focus of this project is to research and understand the effects the arts have on both general students and STEM students in particular, what benefits come from art education and art integration, and if STEM students benefit from art integration. This goal was accomplished through a literature review and annotated bibliography featuring 18 sources. Another goal of the project was to understand where I fit into the research. In my creative portion of the project, I explored and analyzed how the arts affected …

A Comparison Of Statistical Methods For Modeling Count Data With An Application To Hospital Length Of Stay, Gustavo Fernandez, Kristina Vatcheva

School of Mathematical & Statistical Sciences Faculty Publications

Background

Hospital length of stay (LOS) is a key indicator of hospital care management efficiency, cost of care, and hospital planning. Hospital LOS is often used as a measure of a post-medical procedure outcome, as a guide to the benefit of a treatment of interest, or as an important risk factor for adverse events. Therefore, understanding hospital LOS variability is always an important healthcare focus. Hospital LOS data can be treated as count data, with discrete and non-negative values, typically right skewed, and often exhibiting excessive zeros. In this study, we compared the performance of the Poisson, negative binomial (NB), …

A Comparative Study On Deep Learning Models For Text Classification Of Unstructured Medical Notes With Various Levels Of Class Imbalance, Hongxia Lu, Louis Ehwerhemuepha, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Background

Discharge medical notes written by physicians contain important information about the health condition of patients. Many deep learning algorithms have been successfully applied to extract important information from unstructured medical notes data that can entail subsequent actionable results in the medical domain. This study aims to explore the model performance of various deep learning algorithms in text classification tasks on medical notes with respect to different disease class imbalance scenarios.

Methods

In this study, we employed seven artificial intelligence models, a CNN (Convolutional Neural Network), a Transformer encoder, a pretrained BERT (Bidirectional Encoder Representations from Transformers), and four typical …

A Push For Inclusive Data Collection In Stem Organizations, Nicholas P. Burnett, Alyssa M. Hernandez, Emily E. King, Richelle L. Tanner, Kathryn Wilsterman

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Professional organizations in STEM (science, technology, engineering, and mathematics) can use demographic data to quantify recruitment and retention (R&R) of underrepresented groups within their memberships. However, variation in the types of demographic data collected can influence the targeting and perceived impacts of R&R efforts - e.g., giving false signals of R&R for some groups. We obtained demographic surveys from 73 U.S.-affiliated STEM organizations, collectively representing 712,000 members and conference-attendees. We found large differences in the demographic categories surveyed (e.g., disability status, sexual orientation) and the available response options. These discrepancies indicate a lack of consensus regarding the demographic groups that …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

Multi-Modality Automatic Lung Tumor Segmentation Method Using Deep Learning And Radiomics, Siqiu Wang

Theses and Dissertations

Delineation of the tumor volume is the initial and fundamental step in the radiotherapy planning process. The current clinical practice of manual delineation is time-consuming and suffers from observer variability. This work seeks to develop an effective automatic framework to produce clinically usable lung tumor segmentations. First, to facilitate the development and validation of our methodology, an expansive database of planning CTs, diagnostic PETs, and manual tumor segmentations was curated, and an image registration and preprocessing pipeline was established. Then a deep learning neural network was constructed and optimized to utilize dual-modality PET and CT images for lung tumor segmentation. …

Investigating The Uncertainties In Ct Non-Small Cell Lung Cancer Radiomics, Gary Ge

Theses and Dissertations--Radiation Medicine

Radiomics is a technique that extracts quantitative features, termed radiomic features, from medical images using data-characterization algorithms. These radiomic features can be used to identify tissue characteristics and radiologic phenotyping that are not observable by clinicians in a non-invasive, low-cost manner, potentially generating image biomarkers for clinical decision. To date, there are still many uncertainties involved in radiomics which limit its clinical implementation. Herein, we propose to explore the impact of each component in the radiomics pipeline on predicting clinical outcomes. In Chapter II, we conduct a thorough review of CT lung cancer radiomics studies to examine the typical feature …

Application Of Competitive Intelligence For Insular Territories: Automatic Analysis Of Scientific And Technology Trends To Fight The Negative Effects Of Climate Change, Henri Dou, Pierre Fournie

International Journal of Islands Research

Islands are fragile territories because of their geographical position. As a result, climate impacts can have serious consequences, of which some are irreversible. Therefore, it is necessary to allow insular territories to benefit from the latest scientific and technological advances in combating climate effects. The current article shows how to deal with automatic analysis of scientific information on the one hand, but also its applications via patents. We will analyse the latest scientific results as well as their possible applications using patent analysis. We will also focus on experts, laboratories, and leading companies, that are active on the field. The …