Medicine and Health Sciences Commons^™

Applying Data Science And Machine Learning To Understand Health Care Transition For Adolescents And Emerging Adults With Special Health Care Needs, Lisamarie Turk

Nursing ETDs

A problem of classification places adolescents and emerging adults with special health care needs among the most at risk for poor or life-threatening health outcomes. This preliminary proof-of-concept study was conducted to determine if phenotypes of health care transition (HCT) for this vulnerable population could be established. Such phenotypes could support development of future studies that require data classifications as input. Mining of electronic health record data and cluster analysis were implemented to identify phenotypes. Subsequently, a machine learning concept model was developed for predicting acute care and medical condition severity. Three clusters were identified and described (Cluster 1, n …

Host-Pathogen Interactions In A Changing World: Microbes, Mucosal Defenses, And Multiple Hosts, Brandon C. Labumbard

Graduate Doctoral Dissertations

As fungal diseases continue to emerge, research increasingly focuses on host-microbiome interactions and links to disease. Certain skin-associated microbes may benefit hosts by protecting them from invading pathogens. Seasonal changes in the host environment can also result in shifts in the microbial community and pathogen virulence – potentially influencing disease dynamics. I investigated how cutaneous microbial communities differ across hosts, seasons, and Batrachochytrium dendrobatidis (Bd) infection status by sequencing the microbial communities of 1,100 leopard frogs at five locations across the US. Percent anti-Bd function varied seasonally and with Bd infection status. Bacterial communities also varied across locations and time. …

Speciated Isotope Dilution Mass Spectrometry In Combination With Thor’S Hammer Metaspike Technology For The Assessment Of Low-Level Biomarkers For Human Health Evaluation, Ashley Ebert

Electronic Theses and Dissertations

Our research team has been focused on quantifying important biological analytes in human blood samples to delineate the biochemical processes underlying certain states of dysfunction and evaluate treatment efficacy. These efforts have been guided by laboratory measurements with the input of medical experts. Speciated isotope dilution mass spectrometry (SIDMS) explained in detail in EPA Method 6800 has been successfully applied in the quantification of an important biomarker analyte for immune function and detoxification processes: glutathione. Past research has proven the molecule a biomarker for autism spectrum disorder (ASD) in the form of the reduced/oxidized glutathione (GSH/GSSG) ratio, and literature has …

An Imaging Mass Spectrometry Investigation Into The N-Linked Glycosylation Landscape Of Pancreatic Ductal Adenocarcinoma And The Development Of Associated Tools For Enhanced Glycan Separation And Characterization, Colin Mcdowell

MUSC Theses and Dissertations

The severity of pancreatic ductal adenocarcinoma (PDAC) is largely attributed to a failure to detect the disease before metastatic spread has occurred. CA19-9, a carbohydrate biomarker, is used clinically to surveille disease progression, but due to specificity challenges is not suitable for early discovery. As CA19-9 and other prospective markers are glycan epitopes, there is great clinical interest in understanding the glycobiology of pancreatic cancer. Unfortunately, few studies have been able to link glycosylation changes directly to pancreatic tumors and instead have focused on peripheral glycan alterations in the serum of PDAC patients. To address this gap in our understanding, …

Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak

Honors Capstones

In this research project, natural language processing techniques’ ability to accurately classify medical text was measured to reinforce the relevance of artificial intelligence in the medical field. Sentiment analyses (analyses to determine whether the text was positive or negative) were performed on the prescription drug reviews in an open-source dataset using four different models: lexical, a neural network, a support vector machine, and a logistic regression model. Each model’s effectiveness was gauged by its ability to correctly classify unlabeled drug reviews (i.e., a percentage representing accuracy). The machine learning models were able to accurately classify the text, while the lexical …

Intra-Skeletal Variation In Stable Isotopes Through Non-Destructive Approaches: Applications Of The Patterns Of Skeletal Remodeling To Biological Anthropology, Armando Anzellini

Doctoral Dissertations

Stable isotope analysis is a well-established method in biological anthropology used to deliver data on residence, diet, and life history. Samples for these analyses are often collected from the diaphyses of long bones with an assumption of an expected rate of turnover between five and ten years, depending on the skeletal element. However, the biological foundations of this assumption are still uncertain, especially concerning the intra-skeletal and intra-element variation of isotopic signatures that may relate to patterns of remodeling. Exploring these gaps in intra-element isotopic variation requires fine-grained work using multiple bones from multiple individuals, but such work is limited …

Use Of Healthcare Utilization Records For Analyzing Trends In Clinical Toxoplasmosis: A Comparison Of Nevada And The United States, Elijah Kreutzer

UNLV Theses, Dissertations, Professional Papers, and Capstones

Toxoplasmosis, a zoonotic disease caused by the parasitic protist Toxoplasma gondii, is a ubiquitous, global public health concern with a wide variety of clinical manifestations. Surveillance for the disease is lacking even in developed countries, and what surveillance is present most often focuses on pregnant women. This research investigated trends in clinical toxoplasmosis in Nevada and nationally to address the lack of knowledge concerning how Nevada discharges compare to national discharges in cases of toxoplasmosis. Specifically, this research sought to determine what characterizes toxoplasmosis in Nevada across inpatient, outpatient, and emergency department settings, as well as how these cases differ …

Smartphone As An Edge For Context-Aware Real-Time Processing For Personal E-Health, Muhammad Bangash

University Honors Program Senior Projects

The medical domain is facing an ongoing challenge of how patients can share their health information and timeline with healthcare providers. This involves secure sharing, diverse data types, and formats reported by healthcare-related devices. A multilayer framework can address these challenges in the context of the Internet of Medical Things (IoMT). This framework utilizes smartphone sensors, external services, and medical devices that measure vital signs and communicate such real-time data with smartphones. The smartphone serves as an “edge device” to visualize, analyze, store, and report context- aware data to the cloud layer. Focusing on medical device connectivity, mobile security, data …

Quantifying The Magnitude Of Total Dose Deviation Caused By Various Sources Of Error Among Iroc Phantom Irradiation Results, Sharbacha S. Edward

Dissertations & Theses (Open Access)

The Imaging and Radiation Oncology Core (IROC) phantoms are used as an end-to-end test of an institution’s radiotherapy processes, and for clinical trial credentialing. Phantoms are treated like patients, and evaluation of the doses received by the thermoluminescent dosimeters (TLDs) inside the phantom, reflects the accuracy with which an institution can image, plan and irradiate a phantom or patient. Recent phantom results show that among the hundreds of various IROC phantoms irradiated annually, 8-17% of institutions fail this test. The purpose of this work was to investigate the various types of errors that may occur during the treatment process and …

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Evaluating The Health Impacts Of Fruit And Vegetable Intake At The Individual Level And Food Pantry Level Among Food Pantry Users, Jiacheng Chen

Legacy Theses & Dissertations (2009 - 2024)

Background: Chronic diseases impose heavy burdens on individuals and the healthcare system in the US. Many factors were found to be associated with chronic diseases, including demographics, family history, social environmental factors, and individual behavioral factors such as diet and physical activity. Among those factors, fruit and vegetable intake can have substantial health impacts via a variety of causal pathways. Fruit and vegetable (F&V) consumption is generally lower among individuals living in households experiencing food insecurity and rely on food assistance programs. Decreased F&V intake among food pantry users may negatively impact health. However, conducting quantitative analysis on this population …

Metabolic Alterations And Cardiovascular Risk After Hepatitis C Cure In Subjects With Or At Risk For Hiv, Christophe Maxime Fokoua Dongmo

Legacy Theses & Dissertations (2009 - 2024)

Background. Hepatitis C virus (HCV) infection engenders substantial metabolic changes. These changes are altered when the virus is cleared after successful treatment. We measured these metabolic alterations that occur after HCV cure; further, we assessed whether these alterations differed in subgroups defined by patients’ characteristics.

Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury

Electronic Theses and Dissertations

Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …

Alpha, Beta-Unsaturated Aldehydes: The Underrepresented Markers Of Disease., Saurin Sutaria

Electronic Theses and Dissertations

The peroxidation of unsaturated fatty acids is a widely recognized metabolic process that creates a complex mixture of volatile organic compounds including aldehydes. Elevated levels of reactive oxygen species in cancer cells promote random lipid peroxidation, which leads to an increase in a variety of aldehydes. Many of these volatile aldehydes are exhaled and are of interest as potential markers of disease. Chapter 1 presents a review of reported aldehydes in the exhaled breath of lung cancer patients. alpha,beta-Unsaturated aldehydes, detected primarily when derivatized during exhaled breath preconcentration, are underreported in the reviewed articles. Chapter 1 concludes with our hypothesis …

A Multiple Input Multiple Output Framework For The Automatic Optical Fractionator-Based Cell Counting In Z-Stacks Using Deep Learning, Palak Dave

USF Tampa Graduate Theses and Dissertations

Quantifying cells in a defined region of biological tissue is critical for many clinical and preclinical studies, especially in pathology, toxicology, cancer, and behavior. Unbiased stereology is the state-of-art method for quantification of the total number and other morphometric parameters of stained objects in a defined region of biological tissue. As part of a program to develop accurate, precise, and more efficient automatic approaches for quantifying morphometric changes in biological tissue, our group has shown that both deep learning-based and hand-crafted algorithms can estimate the total number of histologically stained cells at their maximal profile of focus in extended depth …

Science, Technology, Engineering, And Mathematics (Stem) Project-Based Learning (Pbl) Education: A New Mexico Case Study For Equity And Inclusion, Kimberly A. Scheerer

Teacher Education, Educational Leadership & Policy ETDs

This research addresses how student participation in Science, Technology, Engineering, and Mathematics (STEM) project-based learning (PBL) education activities encourages underrepresented minority student achievement in STEM career field trajectories. Seven New Mexico high school counselors and 12 STEM organization personnel were interviewed during this study. Their responses represent the nuanced professional voices where New Mexico public education intersects with STEM student interest and cultural influence.

For students, STEM PBL can foster deep integration across educational disciplines and enhance STEM career trajectory interest and readiness. STEM education converged with PBL methodologies has the ability to leverage community support while broadening student networks. …

Exploration Of Occupational Safety And Health In Pakistan's Ship Breaking And Recycling Industry, Shehzad Akbar

World Maritime University Dissertations

No abstract provided.

Unobtrusive Assessment Of Upper-Limb Motor Impairment Using Wearable Inertial Sensors, Brandon R. Oubre

Doctoral Dissertations

Many neurological diseases cause motor impairments that limit autonomy and reduce health-related quality of life. Upper-limb motor impairments, in particular, significantly hamper the performance of essential activities of daily living, such as eating, bathing, and changing clothing. Assessment of impairment is necessary for tracking disease progression, measuring the efficacy of interventions, and informing clinical decision making. Impairment is currently assessed by trained clinicians using semi-quantitative rating scales that are limited by their reliance on subjective, visual assessments. Furthermore, existing scales are often burdensome to administer and do not capture patients' motor performance in home and community settings, resulting in a …

Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian

Doctoral Dissertations

The self-assembly of charged macromolecules forms the basis of all life on earth. From the synthesis and replication of nucleic acids, to the association of DNA to chromatin, to the targeting of RNA to various cellular compartments, to the astonishingly consistent folding of proteins, all life depends on the physics of the organization and dynamics of charged polymers. In this dissertation, I address several of the newest challenges in the assembly of these types of materials. First, I describe the exciting new physics of the complexation between polyzwitterions and polyelectrolytes. These materials open new questions and possibilities within the context …

Accelerating Multiparametric Mri For Adaptive Radiotherapy, Shraddha Pandey

USF Tampa Graduate Theses and Dissertations

MR guided Radiotherapy (MRgRT) marks an important paradigm shift in the field of radiotherapy. Superior tissue contrast of MRI offers better visualization of the abnormal lesions, as a result precise radiation dose delivery is possible. In case of online treatment planning, MRgRT offers better control of intratumoral motion and quick adaptation to changes in the gross tumor volume. Nonetheless, the MRgRT process flow does suffer from some challenges that limit its clinical usability. The primary aspects of MRgRT workflow are MRI acquisition, tumor delineation, dose map prediction and administering treatment. It is estimated that the acquisition of MRI takes around …

Respiratory Pattern Analysis For Covid-19 Digital Screening Using Ai Techniques, Annita Tahsin Priyoti

Electronic Thesis and Dissertation Repository

Corona Virus (COVID-19) is a highly contagious respiratory disease that the World Health Organization (WHO) has declared a worldwide epidemic. This virus has spread worldwide, affecting various countries until now, causing millions of deaths globally. To tackle this public health crisis, medical professionals and researchers are working relentlessly, applying different techniques and methods. In terms of diagnosis, respiratory sound has been recognized as an indicator of one’s health condition. Our work is based on cough sound analysis. This study has included an in-depth analysis of the diagnosis of COVID-19 based on human cough sound. Based on cough audio samples from …

Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros

McKelvey School of Engineering Theses & Dissertations

Proton radiotherapy has the potential to treat tumors with better conformal dose distribution than competing modalities when the rapid dose falloff at the end of the proton-beam range is correctly aligned to the edge of the clinical target volume (CTV). However, its clinical potential is dependent on the accurate localization of the Bragg-peak position from predicted stopping-power ratio maps. The method that is most commonly used in today’s clinical practice for predicting stopping-power ratio (SPR) consists of a stoichiometric calibrationtechnique based on single-energy CT (SECT) for direct estimation of patient-specific SPR distribution from vendor-reconstructed Hounsfield Unit (HU) images. Unfortunately, this …

Exploration In Mental Performance For Division 1 Sec College Football Student Athletes, Alex Burgdorf

Department of Occupational Therapy Entry-Level Capstone Projects

The stigma surrounding mental health in sports has made intervention difficult. “There is a need for various actors to provide more effective strategies to overcome the stigma that surrounds mental illness, increase mental health literacy in the athlete/coach community, and address athlete-specific barriers to seeking treatment for mental illness” (Castadelli-Maia et.al 2019). The athletes in the football program at the University of Tennessee face more pressure today than ever in history. They have their class schedule, practice and training every day, and meetings with their position coaches. Now, with the introduction of name, image, and likeness (NIL) allowing players to …

Pipeline For Calculating Calories For Print Recipes With Minimal User Intervention, Karl W. Holten

Theses and Dissertations

The thesis will provide a pipeline to estimate calorie counts from print recipes. The pipeline takes scanned recipes from cookbooks and uses Optical Character Recognition (OCR) to convert the scanned images of recipes to text. Several OCR tools were tested for their accuracy on fractions using a sample of the data, and the most accurate tool is used on the data. Next, a specially trained named entity recognition model is used to identify ingredients, quantities and units. These ingredients are used to search a database of values from the FDA to compute a calorie count for the recipe. The thesis …

Protein-Protein Interaction Prediction From Language Of Biological Coding, Nayan Howladar

University of New Orleans Theses and Dissertations

Protein-protein interactions in a cell are essential to the characterization and performance of various fundamental biological processes. Due to the tedious, resource-expensive, and time-consuming experimental processes, computational techniques to solve protein pair interaction difficulties have emerged as an active research area in bioinformatics. This research seeks to develop an innovative machine learning-based technique that predicts the interaction of a protein pair based on carefully selected input features and exploits information-rich evolutionary information. We developed a protein-protein interaction predictor, PPILS, that leverages the evolutionary knowledge from the protein language model. We examined several distinct neural network architectures: CNN+LSTM, Transformer, Encoder-Decoder, and …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Utilization Of Finite Element Analysis Techniques For Adolescent Idiopathic Scoliosis Surgical Planning, Michael A. Polanco

Mechanical & Aerospace Engineering Theses & Dissertations

Adolescent Idiopathic Scoliosis, a three-dimensional deformity of the thoracolumbar spine, affects approximately 1-3% of patients ages 10-18. Surgical correction and treatment of the spinal column is a costly and high-risk task that is consistently complicated by factors such as patient-specific spinal deformities, curve flexibility, and surgeon experience. The following dissertation utilizes finite element analysis to develop a cost-effective, building-block approach by which surgical procedures and kinematic evaluations may be investigated. All studies conducted are based off a volumetric, thoracolumbar finite element (FE) model developed from computer-aided design (CAD) anatomy whose components are kinematically validated with in-vitro data. Spinal ligament stiffness …

Environmental Communication: Changing The Attitude-Behavioral Gap In Science Communication Utilizing Strategic Messaging, Carrie Helgeson Nelms

Graduate Theses and Dissertations

National Polls in the United States consistently find the public’s beliefs and attitudes about climate change and other environmental issues significantly diverge from those held by the science community. A communication gap between the findings on the causes and effects of environmental issues and the public’s inability to interpret or refuse to accept these findings are possible causes of this divergence. This communication gap constitutes a threat to society because of inaction to environmental problems and points to needed changes in scientific messaging that better informs and motivates behavioral change. The present research employed a strategic message design to affect …

Absolute Quantification Of Tc-99m Activity Distributions Using A Planar Molecular Breast Imaging Commercial System, Benjamin P. Lopez

Dissertations & Theses (Open Access)

Molecular breast imaging (MBI) uses two dedicated-breast semiconductor detectors to visualize the preferential uptake of technetium-99m-sestamibi (^99mTc-sestamibi) by breast cancer cells relative to surrounding benign breast tissues. Clinically, MBI is used primarily as a supplementary tool to standard-of-care mammography because of its improved detection of breast cancers, especially in women with mammographically-dense breasts. Because of a lack of image corrections, MBI applications are currently limited to qualitative evaluations of relative pixel intensities between image regions with suspected lesions and normal tissue.

The objective of this dissertation was to use Monte Carlo simulations to better characterize the MBI imaging …

Identification And Quantitation Of Unspecified Impurities Discovered In Novel Oral Irinotecan By Lc-Ms/Ms And Uhplc, Laura B. Miller

Forensic Science Master's Projects

Irinotecan is a cancer medication approved for medical use in the United States in 1996. It is currently administered via intravenous injection. However, intravenous dosing has disadvantages such as requirement of administration by a trained professional in a medical facility, possible severe adverse effects, pain at the injection site, and possible hemolysis if injected too rapidly. Previously oral administration was not feasible because the p-glycoprotein (p-GP) on the cell membrane of stomach cells acts as a defense mechanism against harmful substances by pumping the irinotecan back into the intestinal lumen for excretion. With the discovery of the p-GP inhibitor encequidar …