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Articles 1 - 15 of 15
Full-Text Articles in Medicine and Health Sciences
Alpha, Beta-Unsaturated Aldehydes: The Underrepresented Markers Of Disease., Saurin Sutaria
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 …
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
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 …
The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah
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 …
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
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 …
Role Of Deep Learning Techniques In Non-Invasive Diagnosis Of Human Diseases., Hisham Abouelseoud Elsayem Abdeltawab
Role Of Deep Learning Techniques In Non-Invasive Diagnosis Of Human Diseases., Hisham Abouelseoud Elsayem Abdeltawab
Electronic Theses and Dissertations
Machine learning, a sub-discipline in the domain of artificial intelligence, concentrates on algorithms able to learn and/or adapt their structure (e.g., parameters) based on a set of observed data. The adaptation is performed by optimizing over a cost function. Machine learning obtained a great attention in the biomedical community because it offers a promise for improving sensitivity and/or specificity of detection and diagnosis of diseases. It also can increase objectivity of the decision making, decrease the time and effort on health care professionals during the process of disease detection and diagnosis. The potential impact of machine learning is greater than …
Spectroscopic Measurements Of Meibum Compositional, Structural, And Functional Relationships To Elucidate The Role Of Meibum In Dry Eye., Anthony Chigozie Ewurum
Spectroscopic Measurements Of Meibum Compositional, Structural, And Functional Relationships To Elucidate The Role Of Meibum In Dry Eye., Anthony Chigozie Ewurum
Electronic Theses and Dissertations
The major aim of my dissertation was to investigate the etiology of dry eye disease which affects about 7 million people in the United States, causing symptoms that can lead to visual disturbance. Correlation between dry eye and an abnormal lipid layer of the tear film has been found. Tear film lipids originate mostly from the meibomian glands. Cholesteryl ester (CE) and Wax ester (WE) lipids make up most of the human meibum lipidome and the CE/WE ratio has been shown to decrease in patients with meibomian gland dysfunction. Model studies using synthetic CE and WE, although providing some insight, …
Multilateration Index., Chip Lynch
Multilateration Index., Chip Lynch
Electronic Theses and Dissertations
We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Electronic Theses and Dissertations
Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …
Innate Immunity, The Hepatic Extracellular Matrix, And Liver Injury: Mathematical Modeling Of Metastatic Potential And Tumor Development In Alcoholic Liver Disease., Shanice V. Hudson
Innate Immunity, The Hepatic Extracellular Matrix, And Liver Injury: Mathematical Modeling Of Metastatic Potential And Tumor Development In Alcoholic Liver Disease., Shanice V. Hudson
Electronic Theses and Dissertations
The overarching goals of the current work are to fill key gaps in the current understanding of alcohol consumption and the risk of metastasis to the liver. Considering the evidence this research group has compiled confirming that the hepatic matrisome responds dynamically to injury, an altered extracellular matrix (ECM) profile appears to be a key feature of pre-fibrotic inflammatory injury in the liver. This group has demonstrated that the hepatic ECM responds dynamically to alcohol exposure, in particular, sensitizing the liver to LPS-induced inflammatory damage. Although the study of alcohol in its role as a contributing factor to oncogenesis and …
Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor
Electronic Theses and Dissertations
Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …
Generalized Spatiotemporal Modeling And Causal Inference For Assessing Treatment Effects For Multiple Groups For Ordinal Outcome., Soutik Ghosal
Generalized Spatiotemporal Modeling And Causal Inference For Assessing Treatment Effects For Multiple Groups For Ordinal Outcome., Soutik Ghosal
Electronic Theses and Dissertations
This dissertation consists of three projects and can be categorized in two broad research areas: generalized spatiotemporal modeling and causal inference based on observational data. In the first project, I introduce a Bayesian hierarchical mixed effect hurdle model with a nested random effect structure to model the count for primary care providers and understand their spatial and temporal variation. This study further enables us to identify the health professional shortage areas and the possible impacting factors. In the second project, I have unified popular parametric and nonparametric propensity score-based methods to assess the treatment effect of multiple groups for ordinal …
Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller
Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller
Electronic Theses and Dissertations
The inherent heterogeneity of tumor tissue presents a major challenge to nanoparticle-medicated drug delivery. This heterogeneity spans from the molecular to the cellular (cell types) and to the tissue (vasculature, extra-cellular matrix) scales. Here we employ computational modeling to evaluate therapeutic response as a function of vascular-induced tumor tissue heterogeneity. Using data with three-layered gold nanoparticles loaded with cisplatin, nanotherapy is simulated with different levels of tissue heterogeneity, and the treatment response is measured in terms of tumor regression. The results show that tumor vascular density non-trivially influences the nanoparticle uptake and washout, and the associated tissue response. The drug …
Designing Interactive Virtual Environments With Feedback In Health Applications., Yi Li
Designing Interactive Virtual Environments With Feedback In Health Applications., Yi Li
Electronic Theses and Dissertations
One of the most important factors to influence user experience in human-computer interaction is the user emotional reaction. Interactive environments including serious games that are responsive to user emotions improve their effectiveness and user satisfactions. Testing and training for user emotional competence is meaningful in healthcare field, which has motivated us to analyze immersive affective games using emotional feedbacks. In this dissertation, a systematic model of designing interactive environment is presented, which consists of three essential modules: affect modeling, affect recognition, and affect control. In order to collect data for analysis and construct these modules, a series of experiments were …
Multipurpose Tenofovir Disoproxil Fumarate Electrospun Fibers For The Prevention Of Hiv-1 And Hsv-2 Infections., Kevin Tyo
Electronic Theses and Dissertations
Sexually transmitted infections affect hundreds of millions of worldwide. Both human immunodeficiency virus (HIV-1 and -2) and herpes simplex virus-2 (HSV-2) remain incurable, urging the development of new prevention strategies. While current prophylactic technologies are dependent on strict user adherence to achieve efficacy, there is a dearth of delivery vehicles that provide discreet and convenient administration, combined with prolonged-delivery of active agents. To address these needs, we created electrospun fibers (EFs) comprised of FDA-approved polymers, poly(lactic-co-glycolic acid) (PLGA) and poly(DL-lactide-co-ε-caprolactone) (PLCL), to provide sustained-release and in vitro protection against HIV-1 and HSV-2. PLGA and PLCL EFs, incorporating the antiretroviral, tenofovir …
Biomarker Discovery Of Liver Diseases Using Mass Spectrometry-Based Metabolomics., Xue Shi
Biomarker Discovery Of Liver Diseases Using Mass Spectrometry-Based Metabolomics., Xue Shi
Electronic Theses and Dissertations
Metabolomics has emerged as one of the latest of the "-omics" disciplines that can detect metabolite biomarkers in biological samples. The diverse characteristics of metabolites make the analytical platform challenging in metabolomics. Two bioanalytical platforms were developed in this study to investigate metabolite abundance changes under different biological conditions. We first developed a bioanalytical platform that coupled linear trap quadruple - Fourier transform ion cyclotron mass spectrometer (LTQ-FTICR MS) with direct infusion chip-based nano-electrospray ionization (DI-nESI) and applied it to study polychlorinated biphenyls (PCB) effects on non-alcoholic fatty liver disease (NAFLD). We also employed this platform in conjunction with in …