Medicine and Health Sciences Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Development Of Graphical Models And Statistical Physics Motivated Approaches To Genomic Investigations, Yashwanth Lagisetty

Dissertations & Theses (Open Access)

Identifying genes involved in disease pathology has been a goal of genomic research since the early days of the field. However, as technology improves and the body of research grows, we are faced with more questions than answers. Among these is the pressing matter of our incomplete understanding of the genetic underpinnings of complex diseases. Many hypotheses offer explanations as to why direct and independent analyses of variants, as done in genome-wide association studies (GWAS), may not fully elucidate disease genetics. These range from pointing out flaws in statistical testing to invoking the complex dynamics of epigenetic processes. In the …

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

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 …

Developing Artificial Intelligence And Machine Learning To Support Primary Care Research And Practice, Jacqueline K. Kueper

Electronic Thesis and Dissertation Repository

This thesis was motivated by the potential to use "everyday data", especially that collected in electronic health records (EHRs) as part of healthcare delivery, to improve primary care for clients facing complex clinical and/or social situations. Artificial intelligence (AI) techniques can identify patterns or make predictions with these data, producing information to learn about and inform care delivery. Our first objective was to understand and critique the body of literature on AI and primary care. This was achieved through a scoping review wherein we found the field was at an early stage of maturity, primarily focused on clinical decision support …

Leveraging Context Patterns For Medical Entity Classification, Garrett Johnston

Computer Science Senior Theses

The ability of patients to understand health-related text is important for optimal health outcomes. A system that can automatically annotate medical entities could help patients better understand health-related text. Such a system would also accelerate manual data annotation for this low-resource domain as well as assist in down- stream medical NLP tasks such as finding textual similarity, identifying conflicting medical advice, and aspect-based sentiment analysis. In this work, we investigate a state-of-the-art entity set expansion model, BootstrapNet, for the task of medical entity classification on a new dataset of medical advice text. We also propose EP SBERT, a simple model …

The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina

Student Theses and Dissertations

Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.

Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …

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 …

Building An Artificial Intelligence Framework For Hypertension Diagnosis: A Use Case Of The Problem List Curation, Ketemwabi Yves Shamavu

Theses & Dissertations

Hypertension is the world's leading factor in cardiovascular disease. Forty-seven percent or close to one in two Americans aged 18 and older are affected. It predicts approximately a thousand deaths per day. Based on recent statistics from the Centers for Disease Control and Prevention, one in three patients with hypertension does not know they are hypertensive. Seventy-five percent of hypertensive patients have uncontrolled hypertension - meaning that they are not treated to target. While there is extensive literature on hypertension diagnosis and management, there is an apparent gap in understanding and acknowledging that a person is hypertensive. Moreover, blood pressure …

Covid Synergy: A Machine Learning Approach Uncovering Potential Treatment Combinations For Sars-Cov-2, Jason Eden Sanchez

Open Access Theses & Dissertations

For more than two years, the COVID-19 pandemic has upended the lives of billions of individualsworldwide leading to disruptions in healthcare, the economy and society at large. As the pandemic enters its third year, the human impact cannot be overstated and the need to develop effective pharmaceuticals remains. Though there currently exits FDA-approved medications for COVID-19, the emergence of novel variants, such as Omicron, highlights the importance of discovering new therapies which will continue to be effective regardless of the pandemicâ??s progression. Because discovering new medications is a costly and timeintensive endeavor, my approach entails drug repurposing to test medications …

Patient Centric Solutions To Mitigate Information Need Of Obstetric Ultrasound Exam Among Pregnant Women: Design-Thinking Approach, Eman Alanazi

Theses and Dissertations

Design thinking approach is an approach used widely to solve problems by providing innovative solutions. In this dissertation I focused on the user experience research filed where I designed new obstetric ultrasound reports by adopting the design thinking approach to reach the main goal of the dissertation which is mitigating pregnant women information needs about obstetric ultrasound exam and improve their understanding and knowledge about the obstetric ultrasound report and the exam. I developed two versions of new designed report called SPOUR (Smart Patient-Oriented Obstetric Ultrasound Report). We have conducted five studies to reach the dissertation goal and designed two …

Video Games, Grief, And The Character Link System, Nam Nguyen

University of New Orleans Theses and Dissertations

Grief can encompass more than just the loss of real-life people. It can be felt with the loss of a pet, changes in daily structure, and even the loss of video game characters. The topic of grief related to video games and video game characters comes at a time when games as a service (GaaS) continue to increase in popularity and the phenomenon where these games also inevitably terminate service. To combat this unique form of grief, the Character LINK System was created as a tool that uses simple natural language processing (NLP) techniques to offer support to the bereaved …

Studying Alive : An Application For The Wellness Of College Students During The Covid-19 Pandemic, Natasia Fernandez

Theses, Dissertations and Culminating Projects

Mental health awareness has become an increasingly important topic over the past couple of years due the Covid-19 pandemic. Many individuals find it difficult to discuss their mental health. An individual’s mental health is a significant factor in maintaining their overall wellness. College students, specifically, face various hurdles and challenges that can affect their mental health. They have several responsibilities weighing on their shoulders which can lead to stress, depression and/or anxiety. College students may find it difficult to express these topics and seek healthy ways to cope. During the Covid-19 pandemic, additional challenges have been added onto college students …

Modeling Of Cns Cancer With A Focus On The Immune Component, Daniel Zamler

Dissertations & Theses (Open Access)

The knowledge surrounding cancers of the central nervous system remains poorly developed, in particular with regard to the immune component. The works contained in this thesis look at craniopharyngioma, glioblastoma, and several forms of brain metastasis. While some attention is given to the tumor cells themselves, as well as the patient setting which these studies model, the immune component of disease progression and treatment plays a strong role in each and is the primary focus of the works contained.

Craniopharyngioma is a relatively rare tumor in adults. Although histologically benign, it can be locally aggressive and may require additional therapeutic …

A Meshless Approach To Computational Pharmacokinetics, Anthony Matthew Khoury

Doctoral Dissertations and Master's Theses

The meshless method is an incredibly powerful technique for solving a variety of problems with unparalleled accuracy and efficiency. The pharmacokinetic problem of transdermal drug delivery (TDDD) is one such topic and is of significant complexity. The locally collocated meshless method (LCMM) is developed in solution to this topic. First, the meshless method is formulated to model this transport phenomenon and is then validated against an analytical solution of a pharmacokinetic problem set, to demonstrate this accuracy and efficiency. The analytical solution provides a locus by which convergence behavior are evaluated, demonstrating the super convergence of the locally collocated meshless …

On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández

USF Tampa Graduate Theses and Dissertations

Approximately 33 million American adults had a movement disorder associated with medication use, ear infections, injury, or neurological disorders in 2008, with over 18 million people affected by neurological disorders worldwide. Physical therapists assist people with movement disorders by providing interventions to reduce pain, improve mobility, avoid surgeries, and prevent falls and secondary complications of neurodegenerative disorders. Current gait assessments used by physical therapists, such as the Multiple Sclerosis Walking Scale, provide only semi-quantitative data, and cannot assess walking quality in detail or describe how one’s walking quality changes over time. As a result, quantitative systems have grownas useful tools …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Usability Of Health-Related Websites By Filipino-American Adults And Nursing Informatics Experts, Kathleen Begonia

Dissertations, Theses, and Capstone Projects

Filipino-Americans are an understudied minority group with high prevalence and mortality from chronic conditions, such as cardiovascular disease and diabetes. Facing barriers to care and lack of culturally appropriate health resources, they frequently use the internet to obtain health information. It is unknown whether they perceive health-related websites to be useful or easy to use because there are no published usability studies involving this population. Using the Technology Acceptance Model as a theoretical framework, this study investigated the difference between website design ratings by experts and the perceptions of Filipino-American users to determine if usability guidelines influenced the perceived ease …

Building A Learning Healthcare System: A Path To Optimizing Big Health Data To Inform Clinical Care Decisions, Danne Charlotte Emily Elbers

Graduate College Dissertations and Theses

The explosive growth of data and computing power of the last decades has had large impacts on a myriad of domains, not in the least on one of society’s most complex systems: healthcare. In this work, a version of the resulting Learning Healthcare System (LHS) is explored and elements of it have been implemented and are in use at the Department of Veterans’ Affairs today. After an overview of what a LHS is and what it could be once executed in its full form, the chapters will describe in detail some of the individual elements and how they address cogs …

Modeling The Heterogeneous Temporal Dynamics Of Epidemics On Networks, Andrea Joan Allen

Graduate College Dissertations and Theses

Mathematical models of infectious disease are important tools for understanding large-scale patterns of how a disease spreads through a population. Predictions of trends from disease models help guide public health prevention and mitigation measures. Most simple disease models assume that the population is randomly mixed, but real-world populations exhibit heterogeneous patterns in the way people interact. These differences in population structure can be represented by networks. Networks can then be incorporated into disease models by using various interdisciplinary concepts and tools. Yet even network disease models often overlook that populations change over time. In this thesis, two models of infectious …

Website Accessibility Strategies, Gary W. Hrezo

Walden Dissertations and Doctoral Studies

Most websites cannot be readily used by people with disabilities, despite the internet being an essential component for people to be part of a community. Applying web accessibility strategies means that people with disabilities can better interact with the web. Grounded in Davis’s technology acceptance model, the purpose of this qualitative multiple case study was to examine strategies used by web designers to make websites accessible for people with disabilities. The participants were experienced web developers from organizations in Florida with websites that have a Web Content Accessibility Guidelines Level 2 of three levels, i.e., AA- rating. The data collection …

Exploring Implementation Strategies Of Iot Technology In Organizations: Technology, Organization, And Environment, Khanhhung Hoang Pham

Walden Dissertations and Doctoral Studies

AbstractAfter organizations successfully adopt the internet of things (IoT) technology, many corporate information technology (IT) leaders face challenges during the implementation phase. Corporate IT leaders' potential failures in implementing IoT devices may impede organizations from integrating IoT solutions and promoting business benefits. Grounded in technology-organization-environment (TOE) theory, the purpose of this qualitative, pragmatic inquiry study was to explore strategies that corporate IT leaders use to implement IoT technology in their organizations. The participants were six corporate healthcare IT leaders who successfully used implementation strategies for implementing IoT solutions for their organizations. Data were collected using semistructured interviews and industry security …

Relationship Between Information System Success Model Dimensions And Electronic Health Records Use, Gloria Oshegbo

Walden Dissertations and Doctoral Studies

The rise in the use of electronic health records (EHRs) in health care facilities necessitates a standardized tool for evaluating their effectiveness. Delone and McLean’s information system success model (ISSM) was the theoretical foundation, which consists of seven dimensions namely system, information, service qualities, user satisfaction, use, system usefulness, and net benefits. The purpose of this study was to examine EHRs’ efficiency and identify ISSM dimensions that influenced net benefits, the dependent variable. The research questions examined the relationship between dimensions of ISSM and the dimensions that affect net benefits. Participants were recruited using purposeful sampling via social media and …