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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Association Between Use Of Remdesivir And Bradycardia, Gibret Umeukeje
Association Between Use Of Remdesivir And Bradycardia, Gibret Umeukeje
USF Tampa Graduate Theses and Dissertations
Remdesivir received the first emergency use authorization from the FDA for the treatment of COVID-19. Multiple adverse drug reactions (ADR) have been reported since its approval in October 2020. Bradycardia, defined by a decrease in heart rate has been reported as an adverse event for patients receiving remdesivir for COVID-19 treatment. The purpose of the research is to systematically investigate the frequency of occurrence of bradycardia in adults receiving remdesivir using clinical data derived from the FDA Adverse Event Reporting System (FAERS) database. Patients receiving remdesivir were compared to those receiving Paxlovid, Regen-Cov, and Dexamethasone for COVID-19 treatment to see …
Data-Driven Analytical Predictive Modeling For Pancreatic Cancer, Financial & Social Systems, Aditya Chakraborty
Data-Driven Analytical Predictive Modeling For Pancreatic Cancer, Financial & Social Systems, Aditya Chakraborty
USF Tampa Graduate Theses and Dissertations
Pancreatic cancer is one of the most deathly disease and becoming an increasingly commoncause of cancer mortality. It continues giving rise to massive challenges to clinicians and cancer researchers. The combined five-year survival rate for pancreatic cancer is extremely low, about 5 to 10 percent, owing to the fact that a large number of the patients are diagnosed at stage IV when the disease has metastasized. Our study investigates if there exists any statistical significant difference between the median survival times and also the survival probabilities of male and female pancreatic cancer patients at different cancer stages, and irrespective of …
Nonparametric Estimation Of Transition Probabilities In Illness-Death Model Based On Ranked Set Sampling, Ying Ma
USF Tampa Graduate Theses and Dissertations
The ranked set sampling (RSS) design is applied widely in agriculture, environmental science, and medical research where the exact measurements of sampling units is costly, but sampling units can be ranked by a correlated concomitant variable. RSS is usually a cost-efficient alternate to simple random sampling (SRS) for selecting more representative samples. This study presents a novel methodology to investigate the nonparametric estimation of transition probabilities in illness-death model using the RSS design. We study the Aalen–Johansen estimator of transition probabilities in illness-death Markov model based on RSS design under random right censoring time and propose nonparametric estimators of the …
New Developments In Statistical Optimal Designs For Physical And Computer Experiments, Damola M. Akinlana
New Developments In Statistical Optimal Designs For Physical And Computer Experiments, Damola M. Akinlana
USF Tampa Graduate Theses and Dissertations
Statistical design of experiments allows for multiple factors influencing a process to be systematically manipulated in an experiment, and their effects on the output of the process to be studied via statistical modeling and analysis. Classical designs offer general nice performance but have limited applications due to restricted design size, region, and randomization structure. Computer generated optimal designs become more popular in recent decades due to the rapid growth in computing power. Most existing work in optimal design of experiments involves designing experiments with optimal performance on a single chosen objective or a single response. However, with the increasing limitation …
Video Anomaly Detection: Practical Challenges For Learning Algorithms, Keval Doshi
Video Anomaly Detection: Practical Challenges For Learning Algorithms, Keval Doshi
USF Tampa Graduate Theses and Dissertations
Anomaly detection in surveillance videos is attracting an increasing amount of attention. Despite the competitive performance of several existing methods, they lack theoretical performance analysis, particularly due to the complex deep neural network architectures used in decision making. Additionally, real-time decision making is an important but mostly neglected factor in this domain. Much of the existing methods that claim to be online, depend on batch or offline processing in practice. Furthermore, several critical tasks such as continual learning, model interpretability and cross-domain adaptability are completely neglected in existing works. Motivated by these research gaps, in this dissertation we discuss our …
A Functional Optimization Approach To Stochastic Process Sampling, Ryan Matthew Thurman
A Functional Optimization Approach To Stochastic Process Sampling, Ryan Matthew Thurman
USF Tampa Graduate Theses and Dissertations
The goal of the current research project is the formulation of a method for the estimation and modeling of additive stochastic processes with both linear- and cycle-type trend components as well as a relatively robust noise component in the form of Levy processes. Most of the research in stochastic processes tends to focus on cases where the process is stationary, a condition that cannot be assumed for the model above due to the presence of the cyclical sub-component in the overall additive process. As such, we outline a number of relevant theoretical and applied topics, such as stochastic processes and …
Using Fine-Scale Aquatic Habitat Data To Construct Dreissenid Sdms In The Laurentian Great Lakes, Grace C. Henderson
Using Fine-Scale Aquatic Habitat Data To Construct Dreissenid Sdms In The Laurentian Great Lakes, Grace C. Henderson
USF Tampa Graduate Theses and Dissertations
The invasion of the Laurentian Great Lakes by aquatic invasive species (AIS) has been the subject of investigation for decades, due to their dramatic alterations to the ecosystem and high economic costs. Two AIS with the largest impacts are dreissenid zebra and quagga mussels, and though these species have been studied extensively, questions remain about what factors control their distributions, and whether lake warming will alter these distributions. Species distribution models (SDMs) offer a powerful tool to examine the relationship between species presences and environmental variables, which are typically bioclimactic data. The creation of the Aquatic Habitat (AqHab) dataset containing …
Measurements Of Generalizability And Adjustment For Bias In Clinical Trials, Yuanyuan Lu
Measurements Of Generalizability And Adjustment For Bias In Clinical Trials, Yuanyuan Lu
USF Tampa Graduate Theses and Dissertations
While randomized controlled trials (RCTs) are widely used as a gold standard in clinical research and public health, they are criticized because of a potential lack of generalizability, as the trial patients may be unrepresentative of the target patient population. Few research addresses how to assess and evaluate the generalizability of RCTs. As we know, patients are rarely selected on a random basis from a well-defined patient population of interest into a clinical trial. Generalizing findings from the RCT samples to the patient population has begun to receive increasing attention. We simulate a patient population with treatment effect size of …