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Articles 1 - 10 of 10
Full-Text Articles in Medicine and Health Sciences
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 …
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 …
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 …
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 …
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 …
The Contribution Of Ethical Governance Of Artificial Intelligence & Machine Learning In Healthcare, Tina Nguyen
The Contribution Of Ethical Governance Of Artificial Intelligence & Machine Learning In Healthcare, Tina Nguyen
Electronic Theses and Dissertations
With the Internet Age and technology progressively advancing every year, the usage of Artificial Intelligence (AI) along with Machine Learning (ML) algorithms has only increased since its introduction to society. Specifically, in the healthcare field, AI/ML has proven to its end-users how beneficial its assistance has been. However, despite its effectiveness and efficiencies, AI/ML has also been under scrutiny due to its unethical outcomes. As a result of this, two polarizing views are typically debated when discussing AI/ML. One side believes that AI/ML usage should continue regardless of its unsureness, while the other side argues that this technology is too …
An Application Of Differential Mathematical Modeling Techniques To Study The Ongoing Rabies Epizootic In China, Christopher Turner
An Application Of Differential Mathematical Modeling Techniques To Study The Ongoing Rabies Epizootic In China, Christopher Turner
Electronic Theses and Dissertations
Rabies remains a global public health issue with a wide variety of neurological symptoms such as confusion, slight paralysis, hypersalivation, and hydrophobia. Rabies is usually fatal once symptoms appear. Many species are reservoirs for rabies, such as foxes, racoons, and wild dogs, which in turn can transmit the disease to humans, leading to complex transmission chains. There is a long latent period of rabies, between 1 to 3 months after infection, which further complicates control efforts. Mathematical modeling is a valuable tool in the study of infectious disease outbreaks and there have been many models applied to rabies outbreaks. However, …
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, …
Modelling Muscle Activation Using Emg Signal, Mercy U. Okonna
Modelling Muscle Activation Using Emg Signal, Mercy U. Okonna
Electronic Theses and Dissertations
(EMG) is a method for measuring muscle activity by an electrical signal, and is useful in studying motor control, postural control, and in physical therapy. A current research topic is creating an algorithm that can use the EMG signal to reliably classify a muscle as active or inactive. This thesis presents a classification algorithm for leg muscles with a single activation spike while walking. Time is rescaled into steps, which are identified using data from cameras measuring joint angles while walking. The algorithm is based on moving averages and a convex combination of mean signal strength in active and inactive …