Medicine and Health Sciences Commons^™

Mapping Climatic And Environmental Determinants Of Parasitic Helminth Prevalence In Southeast Asia, Angelica Avisado

UNLV Theses, Dissertations, Professional Papers, and Capstones

Climate change is reshaping environmental conditions across Southeast Asia (SEA) through rising temperatures, altered precipitation patterns, and increased droughts. These changes alter transmission dynamics of neglected tropical diseases (NTDs) by shifting spatial distribution, increasing larval development rates, faster pathogen growth development, and increasing transmission rates. NTDs are a group of preventable and treatable infections that disproportionately affect more than 1 billion people globally, specifically in tropical and subtropical regions. A subgroup of NTDs, parasitic helminth infections (PHIs) - particularly schistosomiasis, soil-transmitted helminths, and lymphatic filariasis remains a public health concern in the Southeast Asian region. PHIs and their ecological responses …

Ankimedbench: Evaluating Hierarchical Medical Knowledge In Language Model Embeddings, Neel Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Despite achieving over 90% accuracy on medical benchmarks, recent studies show physicians cannot effectively leverage language models to improve clinical reasoning. Current benchmarks test isolated factual recall, but clinical practice requires hierarchical navigation through diagnostic categories—starting broad and narrowing systematically from chest pain to cardiovascular pathology to myocardial infarction to specific STEMI types. Existing evaluations cannot measure whether models preserve this taxonomic structure essential for clinical reasoning.

We introduce AnkiMedBench, built from 16,512 medical flashcards used by students preparing for licensing exams. Cards are organized across six hierarchy levels spanning 16 broad medical specialties to 672 specific diseases and conditions. …

Health Implications Of Heavy Metal Contamination In Commercially Available Deodorant And Antiperspirant Products Sold In Benghazi, Libya, Maysson Yaghi, Khaled Elsherif

Al-Bahir

The extensive usage of deodorants and antiperspirants raises concerns about the potential health risks posed by heavy metal content. This study quantified the levels of five heavy metals: Aluminum, Zirconium, Lead, Cadmium, and Chromium in 22 commercial products widely used in Benghazi, Libya, and assessed the associated health risks. Samples, categorized into gel, stick, and roll-on formulations, were analyzed using iCAP TQ ICP-MS. Al and Zr showed the widest concentration ranges, reflecting their intentional use as active ingredients. Al levels ranged from trace amounts (0.032 mg/kg) up to a maximum of 99.10 mg/kg, while Zr was found exclusively in gel …

Application Of Augmented Reality Technology As A Dietary Monitoring And Control Measure Among Adults: A Systematic Review, Gabrielle Victoria Gonzalez, Bingjing Mao, Ruxin Wang, Wen Liu, Chen Wang, Tung Sung Tseng

School of Public Health Faculty Publications

Background/Objectives: Traditional dietary monitoring methods such as 24 h recalls rely on self-report, leading to recall bias and underreporting. Similarly, dietary control approaches, including portion control and calorie restriction, depend on user accuracy and consistency. Augmented reality (AR) offers a promising alternative for improving dietary monitoring and control by enhancing engagement, feedback accuracy, and user learning. This systematic review aimed to examine how AR technologies are implemented to support dietary monitoring and control and to evaluate their usability and effectiveness among adults. Methods: A systematic search of PubMed, CINAHL, and Embase identified studies published between 2000 and 2025 that evaluated …

Patent Searching With Uspto, Derwent Innovation And Lens.Org, Ibis Anette Moreno-Lozano

Day Family Research Lab Workshop Series

No abstract provided.

White Nose Syndrome In Bats And Infant Mortality In Georgia, Rhys Medcalfe, Sean Medcalfe, Simon Medcalfe

Journal of the Georgia Public Health Association

Background: White nose syndrome (WNS) is a disease in bats caused by the fungus Pseudogymnoascus destructans that can result in bat mortality rates of over 90%. WNS was discovered in Georgia in 2012 in 3 counties but has continued to spread to 14 counties as of 2023, with P. destructans detected in a further seven. Biodiversity loss has been linked to human health outcomes including infant mortality. Understanding the link between WNS, biodiversity loss, and infant mortality in Georgia is important because Georgia ranks 42^nd out of the 50 states for infant mortality rate.

Methods: Using panel data from …

Predicting Skin Concern Severity From Genetic And Lifestyle Factors: A Comparative Multi-Output Machine Learning Framework, Yassine Benachour, Lina Maloukh, Sadok Bouamama, Barbara Geusens

All Works

Personalized dermatology increasingly leverages both genetic predispositions and lifestyle behaviors to model individual skin health outcomes. This study proposes a multi-output machine learning framework to predict the severity of six dermatological phenotypes—acne, redness, dryness, sensitivity, scarring, and pigmentation—using a multimodal dataset of 5,254 individuals. Input features include mutation profiles for six skin-related genes (FLG, MMP1, MMP3, AQP3, SOD2, GPX) and 22 lifestyle variables such as sun exposure, stress, and hydration. We train and evaluate LightGBM models under independent, multi-output, and chained configurations. Performance is assessed using Mean Absolute Error (MAE) and average Quadratic Weighted Kappa (QWK). The proposed ordinal-aware independent …

Enhancing Breast Cancer Detection In Mammographic Imaging Using Explainable Clinical Decision Support System And Framework, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Breast cancer remains one of the leading causes of mortality among women worldwide, where early and precise detection plays a vital role in improving survival rates and treatment outcomes. However, conventional deep learning approaches often encounter challenges in handling dense mammographic tissues and lack transparency in decision-making, limiting their clinical reliability. To address these limitations, this study introduces TransYOLO-GJO, an explainable and optimized detection framework that integrates transformer-based attention mechanisms into the YOLOv9 architecture and leverages the Golden Jackal Optimization (GJO) algorithm for hyperparameter tuning. The transformer encoder enhances contextual feature extraction, particularly in dense breast regions, while GJO dynamically …

Model For Calculating Impact Force For Individualized Hip Fracture Prediction During A Fall, Alisha Agarwal, Daniel Kargilis, Nishtha Gupta, Michael Chang, Rui Feng, Gregory Chang, Chamith S. Rajapakse

Student Papers, Posters & Projects

Osteoporotic-related weakening of bone is a common cause of hip fractures. The standard of care for the diagnosis and management of osteoporosis is the dual-energy x-ray absorptiometry bone mineral density T-scores. Many individuals considered nonosteoporotic, however, still sustain fractures since these tools do not incorporate vital bone parameters and subject-specific characteristics. The purpose of this work was to (1) develop a simple analytical model for estimating the force exerted on the femur during a fall (i.e., impact force) based on measurable patient metrics and (2) define a quantifiable fracture risk index by comparing finite-element-derived bone strength and impact force, which …

Digital Transformation Management And Organizational Performance: The Case Of Albanian Healthcare Sector, Oltjan Hamza

International Journal of Business and Technology

Purpose - The integration of digital technologies into the healthcare system is essential for improving both operational efficiency and quality of services. This study examines the relationship between digital transformation management and organizational performance in the healthcare sector in Albania, with particular focus on the mediating role of leadership in digital transformation and the digital skills of the healthcare staff. Methodology - The study employ a quantitative method through a structured questionnaire using a Likert scale, which was distributed to 93 healthcare sector employees in public and private institutions in Albania. Findings - Data collected through the survey were analyzed …

Selenium Nanoparticles As Versatile Delivery Tools, Amir Nasrolahi Shirazi, Rajesh Vadlapatla, Ajoy Koomer, Kyle Yep, Keykavous Parang

Pharmacy Faculty Articles and Research

Selenium nanoparticles (SeNPs) have emerged as promising metal-based nanoparticles for drug delivery due to their unique physicochemical properties, intrinsic bioactivity, and biocompatibility. SeNPs offer a lower toxicity, higher bioavailability, and flexibility to be customized for surface chemistry compared to traditional selenium compounds. Advances in synthetic strategies, including chemical reduction, green biosynthesis, and surface functionalization with polymers, peptides, or ligands, have improved their stability, targeting capability, and circulation time. SeNP-based systems have demonstrated unique anticancer, antimicrobial, and anti-inflammatory activities, as they can function as drug carriers and active therapeutic agents. The surface of SeNPs has been functionalized with ligands such as …

Unsaturated Fatty Acid Oil-Based Microdroplets: A Promising Novel Class Of Microdroplets, Ramiz S. Alejilat

Seton Hall University Dissertations and Theses (ETDs)

Droplet-based microfluidics has rapidly advanced numerous fields, including chemistry, biology, materials science, medicine, food science, and cosmetics. In these systems, fluorocarbon oil combined with fluorinated surfactants is the preferred medium for fluid encapsulation, offering exceptional stability and biocompatibility essential for sensitive biological and chemical processes. However, growing concerns about the environmental and biological risks associated with fluorinated chemicals have prompted a search for alternatives.

This study is the first to explore the use of unsaturated fatty acids derived from emu oil for microdroplet formation. We characterized droplet formation based on flow rates and the presence non-fluorinated surfactant at a certain …

Understanding Daily Habits Affect On Mood: A Semester-Long Wellness Analysis, Alexis Caitlin Sweeney

Student Scholar Symposium Abstracts and Posters

This research aims to track and assess lifestyle and personal health behaviors over a semester in order to gain a better understanding of how daily routines impact overall well-being. Ten variables are being monitored, including weight, caffeine intake, sleep duration, napping, exercise frequency, homework hours, Instagram screen time, vitamin use, practicing miles, and mood evaluations on a 5-point scale. I intend to identify trends and relationships between these factors through consistent data collection throughout the semester, such as the effects of sleep and caffeine on mood, motivation, and productivity.

As a student-athlete and health science major, this initiative gives me …

Exploring The Potential Of Martian Agriculture: Assessing Viability And Nutritional Composition Of Plants Cultivated In Martian Regolith, Abigail Ross

Honors Theses

In addition to sunlight and water, plants can utilize a small number of nutrients from the soil to biosynthesize all the materials that are needed for growth and development. However, plants require an environment where they are able to obtain those nutrients, such as iron, magnesium, potassium, sulfur, and nitrogen. Environmental factors determine the types and accessibility of nutrients available to plants. Plants then take up these nutrients from the soil to aid in biological mechanisms and the synthesis of important molecules needed for growth and development. Ascorbic acid, commonly known as Vitamin C, is a vital molecule that is …

Understanding Medical Information And Emotional Support Needs In Mental Health Questions With Large Language Models, Chen Liu, William Yu Chung Wang, Gohar Khan

All Works

Purpose – This study seeks to bridge the gap between users’ multidimensional needs and the single-task capabilities of existing Mental Health Question Answering (MHQA) systems by tackling the underexplored challenge of jointly understanding medical informational needs and emotional support needs within complex consumer mental health inquiries. Design/methodology/approach – Grounded in Rhetorical Structure Theory (RST), the proposed Multi-Needs and Context Recognition (MNCR) framework decomposes mental health question understanding task into four interrelated subtasks: Medical Needs Recognition (MNR), Medical Needs-related Context Extraction (MNCE), Emotional Needs Recognition (ENR) and Emotional Needs-related Context Extraction (ENCE). A new benchmark dataset, MHQ-MedEmo, was constructed through multi-layered …

Full Issue, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Synthesis Of Antibody Functionalized Polyaniline/Polystyrene/N-Gqds Composite Fibermats For Sweat Based Cortisol Biosensing Applications, Ashwin James

Honors Theses

Noninvasive, wearable biosensors capable of detecting stress biomarkers in sweat require electrodes that are flexible, conductive, insoluble in water, and highly sensitive at low concentrations of analyte. In this work, bovine serum albumin blocked and anti-cmab immobilized nitrogen doped graphene quantum dots integrated polyaniline/polystyrene composite fibermat electrodes (BSA/Anti-Cmab/N-GQDs/PANI/PS electrodes) were synthesized and evaluated as a potential platform for an electrochemical cortisol biosensor in sweat based systems. Polyaniline was utilized in order to provide electrical conductivity, while polystyrene served as a carrying polymer for mechanical support and its hydrophobicity. Composite fibermats were manufactured through Forcespinning™, followed by a secondary polyaniline graft …

Synthesis And Study Of Stable Organic Radicals For Mri Contrast Agents And New Materials, Sabina Dhakal

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The first part of this dissertation focuses on the design, synthesis, and characterization of a thermally robust S =1/2 phototetrazolinyl monoradical and the development of synthetic methodologies for a high-spin (S = 1) phototetrazolinyl diradical. Electrochemical studies of the phototetrazolium cation (precursor to the monoradical) revealed a remarkably narrow electrochemical band gap (Ecell ≈ 0.82 V), suggesting promising electrical conductivity. Thermal analysis of the monoradical demonstrated excellent stability, with the onset of decomposition at 232 °C. Building on the excellent thermal stability and promising properties for electrical conductivity of the monoradical, we developed two condensation-based synthetic routes that provide viable …

Large-Scale Experimental Study On The Impact Of Air Cleaning & Ventilation On Indoor Air Quality And Student Illness-Related Absenteeism, Daud Nosham

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This large-scale randomized experimental field study investigated the effect of portable air purifiers (PAPs) on classroom’s air quality and student’s illness related absenteeism. PAPs were installed in 317 classrooms from various school districts located in Eastern Nebraska. The classrooms were randomly assigned into four conditions: three treatment conditions (T1, T2 & T3) and one control condition (device without any filter). T1 was equipped with HEPA filters, T2 added Activated Carbon (AC) layer to HEPA, and T3 further integrated Germicidal Ultraviolet (GUV) alongside HEPA and AC filters. The measured variables were carbon dioxide (CO2), fine particles (PN2.5) and coarse particles (PNcoarse), …

A Picture Tells A Thousand Words—, But Ecg Signals Have More To Say, Ashley N. Gomez

Theses and Dissertations

With the increasing adoption of deep learning classification models in the medical domain, a critical challenge remains: achieving high predictive accuracy while maintaining clinical Inter-pretability. This study examines how model architecture, dataset origin, and the use of full versus subset data affect both classification performance and Interpretability in Electrocardiogram (ECG) signal analysis. ResNet18 is evaluated using an open-source ECG Image Dataset, thus a custom dataset derived from digitized ECG images. Post-hoc explainability methods, such as Integrated Gradients, are applied to determine which time steps have the most significant influence on model decisions. The findings demonstrate that model architecture and dataset …

Definition Of The 3d Position And Motion Status Of The Moving Heart Based On 2d Projections, Lawrence D. Orijuela

Electronic Theses, Projects, and Dissertations

This thesis presents a novel application of deep learning to the estimation of pulmonary vein coordinates using X-ray image pairs from a FORBILD Thorax phantom derived motion dataset. A Siamese neural network was developed to predict the 3D coordinates of one pulmonary vein at a time, specifically the Right Superior Pulmonary Vein (RSPV), Left Superior Pulmonary Vein (LSPV), Left Inferior Pulmonary Vein (LIPV), or Right Inferior Pulmonary Vein (RIPV), based on two-dimensional projection images.

The input data consisted of over 1.6 million grayscale X-ray image pairs across 1331 virtual patients, each annotated with ground truth 3D coordinates. To manage memory …

Is Noise Exposure Associated With Impaired Extended High Frequency Hearing Despite A Normal Audiogram? A Systematic Review And Meta-Analysis, Sajana Aryal, Monica Trevino, Hansapani Rodrigo, Srikanta K. Mishra

School of Mathematical & Statistical Sciences Faculty Publications

Understanding the initial signature of noise-induced auditory damage remains a significant priority. Animal models suggest the cochlear base is particularly vulnerable to noise, raising the possibility that early-stage noise exposure could be linked to basal cochlear dysfunction, even when thresholds at 0.25-8 kHz are normal. To investigate this in humans, we conducted a meta-analysis following a systematic review, examining the association between noise exposure and hearing in frequencies from 9 to 20 kHz as a marker for basal cochlear dysfunction. Systematic review and meta-analysis followed PRISMA guidelines and the PICOS framework. Studies on noise exposure and hearing in the 9 …

Short-Term Preeclampsia Prediction: Cutoff Variations For Sflt-1/Plgf In U.S. Patients With Or Without Hypertensive Disorders, Yaxin Li, Kristen Cagino, Jim Yee, Caroline Andy, Dajana Borova, Ayush Shah, Isla Racine, Tracy Grossman, Zhen Zhao

Student Papers, Posters & Projects

BACKGROUND: Preeclampsia (PE) is a complex disorder with significant maternal and fetal risks. The soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) ratio shows promise as a diagnostic tool, but its adoption in the U.S. remains limited due to the lack of accessible testing platforms, U.S.-based studies, and evidence-based implementation guidelines.

PATIENTS/MATERIALS AND METHODS: We conducted a cohort study to evaluate the sFlt-1/PlGF ratio for predicting PE within two weeks among pregnant individuals ≥18 years, ≥20 weeks gestation. Serum samples were obtained from routine prenatal visits or triage evaluations. sFlt-1/PlGF ratios were measured using Roche Elecsys assays, and …

Embedding-Driven Dual-Branch Approach For Accurate Breast Tumor Cellularity Classification, Hossam Magdy Balaha, Ali Mahmoud, Khadiga M. Ali, Mohammed Ghazal, Norah Saleh Alghamdi, Ashraf Khalil, Ayman El-Baz

All Works

This study proposes a dual-branch framework for precise classification of breast tumor cellularity via histopathological images where it integrates two distinct branches: the Embedding Extraction Branch (embedding-driven) and the Vision Classification Branch (vision-based). The Embedding Extraction Branch uses the Virchow2 transformation to generate dense, structured embeddings, whereas the Vision Classification Branch employs Nomic AI Embedded Vision v1.5 to process image patches and produce classification logits. Both branches’ outputs are combined to form the final classification. The framework also suggests Knowledge Block with fully connected layers, batch normalization, and dropout to improve feature extraction and reduce overfitting. The proposed approach reports …

Detection Of Phase-Binning And Interpolation Artifacts In 4-Dimensional Computed Tomography Imaging Using Deep Learning And Rule-Based Approaches, Jorge Cisneros, Nathan H. Feldt, Yevgeniy Vinogradskiy, Richard Castillo, Edward Castillo

Department of Radiation Oncology Faculty Papers

BACKGROUND: Four-dimensional computed tomography (4DCT) imaging is a crucial component to lung cancer radiotherapy planning and enables CT-ventilation-based functional avoidance planning to mitigate radiation toxicity. However, 4DCT scans are frequently impaired by acquisition artifacts that corrupt downstream analyses that depend on lung segmentation and deformable image registration, such as CT-ventilation and dose accumulation.

PURPOSE: This study develops 3D deep learning models to identify phase-binning artifacts at the voxel level and a heuristic, rule-based method to identify interpolation slices within 4DCT images.

METHODS: We introduce a generator that systematically inserts synthetic phase-binning and interpolation artifacts into any artifact-free breathing phase obtained …

Wildfire Smoke And Public Health: Comparing 2023 Canadian Wildfire Events With Hospital Admissions In Douglas County, Nebraska, Jeremy Poell

Capstone Experience: Master of Public Health

Wildfires are becoming increasingly common in Canada and the United States. Smoke produced from these fires creates a multitude of air pollution constituents that can cause breathing and other health issues for humans, particularly those with asthma and other respiratory conditions. Of these pollutants, PM2.5 (particulate matter that is 2.5 microns or smaller) is particularly problematic as these particles are inhaled deep into lung tissue, where they create inflammation and oxidative stress. Poor air quality can also trigger asthma and respiratory issues, leading to an increase in emergency department admissions for breathing treatments. The goal of this study is to …

Real-Time Estimated Sequential Organ Failure Assessment (Sofa) Score With Intervals: Improved Risk Monitoring With Estimated Uncertainty In Health Condition For Patients In Intensive Care Units, Yan He, Qian Luo, Hai Wang, Zhichao Zheng, Haidong Luo, Oon Cheong Ooi

Research Collection Lee Kong Chian School Of Business

Purpose: Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk-scoring systems to aid monitoring, existing systems do not address uncertainties in risk assessments. We developed an enhanced risk monitoring framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring in ICUs.Methods: This study included 5,351 patients admitted to the Cardiothoracic ICU in the National University Hospital in Singapore. We developed machine learning …

Insecticide-Treated Net Use And Elimination Of Malaria In Sub-Saharan African Countries: Assessing The Global Technical Strategy Using An Evolutionary Game Approach, Laxmi, Tamer Oraby, Michael G. Tyshenko, Ina Danquah, Samit Bhattacharyya

School of Mathematical & Statistical Sciences Faculty Publications

Background: Malaria continues to be a major public health challenge in Sub-Saharan Africa (SSA), where the majority of the countries have not met the World Health Assembly's endorsed Global Technical Strategy (GTS) milestones in 2020 for malaria reduction. Insecticide-treated net (ITN) usage is a well-established and effective intervention, often outperforming other measures such as indoor residual spraying (IRS). However, multiple survey studies have reported improper use of ITNs across various SSA countries. This misuse likely poses an important barrier to the intervention's success, although it remains a largely untested hypothesis.

Methods: We developed a behaviour-incidence model and statistical analysis of …

Improving Glycemic Control Among Indonesian Urban Adults: A Digital And Behavioral Extension Of The Information–Motivation–Behavioral Skills Model, Imelda Appulembang

Kesmas

Management of type 2 diabetes mellitus (T2DM) in Indonesia continues to face challenges due to behavioral, informational, and technological gaps among patients. This study analyzed the influence of self-regulatory competence and information, motivation, family support, and digital health literacy on glycemic control behavior. A cross-sectional survey was conducted from February to April 2025 among 587 adults aged >30 years with T2DM enrolled in the Chronic Disease Management Program at primary health care in six major cities: Jakarta, Surabaya, Yogyakarta, Medan, Makassar, and Banjarmasin. Data were collected through structured questionnaires and analyzed using partial least squares structural equation modeling. The findings …

Benchmarking Dna Foundation Models For Genomic And Genetic Tasks, Haonan Feng, Lang Wu, Bingxin Zhao, Chad Huff, Jianjun Zhang, Jia Wu, Lifeng Lin, Peng Wei, Chong Wu

School of Medicine Faculty Publications

The rapid evolution of DNA foundation models promises to revolutionize genomics, yet comprehensive evaluations are lacking. Here, we present a comprehensive, unbiased benchmark of five models (DNABERT-2, Nucleotide Transformer V2, HyenaDNA, Caduceus-Ph, and GROVER) across diverse genomic and genetic tasks including sequence classification, gene expression prediction, variant effect quantification, and topologically associating domain (TAD) region recognition, using zero-shot embeddings. Our analysis reveals that mean token embedding consistently and significantly improves sequence classification performance, outperforming other pooling strategies. Model performance varies among tasks and datasets; while general purpose DNA foundation models showed competitive performance in pathogenic variant identification, they were less …