Health and Medical Administration Commons^™

The Measure Of Efficiency And Effectiveness When Using Artificial Intelligence (Ai) In Radiology, Jordan Watts

Theses, Dissertations and Capstones

Introduction: The use of artificial intelligence in radiology has helped radiologists identify patterns and abnormalities in medical images to diagnose and treat patients. Deep learning and machine learning algorithms have been used to assist physicians in detecting features that are not noticeable to the human eye. The FDA has approved almost 400 AI algorithms for radiology and estimated that the market for AI in medical imaging would grow from $21.48 billion in 2018 to $264.85 billion in 2028.

Purpose of the Study: The purpose of this research was to evaluate the use of artificial intelligence in radiology to determine its …

Outpatient Fall Prevention In Ambulatory Adults 65 Years Old And Over, Dorothy L. Osborne-White

Doctor of Nursing Practice (DNP) Scholarly Projects - Archive

Background: In the United States (U.S.), falls are the leading cause of injury among adults 65 and over, resulting in 36 million falls yearly (Moreland et al., 2020). According to the Centers for Disease Control and Prevention (CDC, 2023), one in four older adults experiences a fall each year. Falls are the world's second most prominent cause of accidental deaths (World Health Organization [WHO], 2021). Falls are the leading cause of both fatal and non-fatal injuries among older adults (Moreland et al., 2020).

Methods: A quality improvement project that included a fall bundle was implemented in a primary clinic. A …

Implementation Of Prognosticator Algorithm For Initiation Of Serious Illness Discussions And Improving The Rate Of Palliative And Hospice Referrals, Joy Isebor

Doctor of Nursing Practice (DNP) Scholarly Projects - Archive

Context: Early serious illness conversations related to end-of-life and goals of care with seriously ill patients have been associated with improving patients' outcomes and quality of care (Bernacki et al., 2015). However, initiating these serious illness discussions has been challenging in the home-based primary care setting.

Objectives: To train and support home-based primary care clinicians in integrating best practices in serious illness discussions and decision-making engagement among patients sixty-five and older with serious illnesses, optimize the alignment between patient goals and the medical care they receive, improving their quality of life and the rate of palliative care and hospice referrals. …

Comparative Analysis Of Machine Learning Models For Predicting Healthcare Traffic: Insights For Optimized Emergency Response, Shadman Mahmood Khan Pathan, Sakan Binte Imran, M. M. Shabab Iqbal, Muhammad Enayetur Rahman, Md. Nurul Absar Siddiky, Muhammad Rezaur Rahman, Md Rafid Hasan, Nondon Lal Dey, Md Sobuj Hossain

Electrical & Computer Engineering Faculty Publications

Efficient management of healthcare traffic is crucial for ensuring timely access to medical services, particularly in emergency situations where delays can have severe consequences. This study presents a comparative analysis of three widely used machine learning models—Linear Regression, Decision Trees, and Random Forests—aimed at predicting healthcare-related traffic volumes. A large dataset from a metropolitan traffic system was used to train and evaluate the models based on key performance indicators, including Mean Squared Error (MSE), R² Score, and computational efficiency. The results reveal that the Random Forest model offers the best performance, achieving higher predictive accuracy and faster execution times compared …

Preparing Healthcare Education For An Ai-Augmented Future, Jiajie Zhang, Susan H Fenton

Faculty, Staff and Student Publications

Artificial intelligence (AI) fundamentally transforms healthcare education as a knowledge enterprise, creating a distributed cognitive system composed of the human brain, which remains relatively unchanged, and AI-based knowledge and cognitive functions, which have accelerated exponentially in scale and power. Education must focus on developing skills to collaborate with AI and on achieving outcomes like problems solved and discoveries made. Curriculum and education policies also need to adapt to this transformation.

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Test Event Example 12/14/23, Metzalli Demolastname

Annual Research Symposium

No abstract provided.

Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler

Dental Hygiene Theses & Dissertations

Purpose: Physiological symptoms and comfort levels while wearing an N95 respiratory mask has not been examined with dental hygienists. The purpose of this study was to investigate dental hygiene students reported physiological symptoms and comfort perception while wearing an N95 respirator mask during patient care appointments. Methods: After IRB approval (IRB #1987754-2), a 16-item questionnaire was distributed through email to a convenience sample of 65 dental hygiene students. Questions assessed respiratory, dermatologic, cardiac, mask mouth and general physiological symptoms, as well as comfort levels. Additionally, participants were asked to respond to demographic questions and one open ended question inquiring about …

Feature Selection From Clinical Surveys Using Semantic Textual Similarity, Benjamin Warner

McKelvey School of Engineering Graduate Student Theses & Dissertations

Survey data collected from human subjects can contain a high number of features while having a comparatively low quantity of examples. Machine learning models that attempt to predict outcomes from survey data under these conditions can overfit and result in poor generalizability. One remedy to this issue is feature selection, which attempts to select an optimal subset of features to learn upon. A relatively unexplored source of information in the feature selection process is the usage of textual names of features, which may be semantically indicative of which features are relevant to a target outcome. The relationships between feature names …

Brief Review: Low Frequency Event Charts (G-Charts) In Healthcare, James Espinosa, David Ho, Alan Lucerna, Henry Schuitema

Rowan-Virtua Research Day

The ability to determine if a change in a system is actually an improvement—or worsening in function—is one of the essential desiderata of quality improvement efforts. There are many ways to look at the issue. A special problem occurs when the event being studied is low frequency by nature. By way of example, patient falls in a given hospital or division of a hospital may occur in a way that is low frequency—yet each event is important. Process engineering has developed an approach to low frequency events. Part of this approach may involve specialized charts that look at the “time-between-events”—as …

Combining Frameworks To Improve Military Health System Quality And Cybersecurity, Dr. Maureen L. Schafer, Dr. Joseph H. Schafer

Military Cyber Affairs

Existing conceptual frameworks and commercially available technology could be considered to rapidly operationalize the use of Quality Measures (QM) within military health systems (Costantino et al. 2020). Purchased healthcare as well as digital healthcare services have paved the way for data collection from multiple information systems thus offering stakeholders actionable intelligence to both guide and measure healthcare outcomes. However, the collection of data secondary to Smart Devices, disparate information systems, cloud services, and the Internet of Medical Things (IOMT) is a complication for security experts that also affect clients, stakeholders, organizations, and businesses delivering patient care. We have combined three …

Enhanced Iot-Based Electrocardiogram Monitoring System With Deep Learning, Jian Ni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Due to the rapid development of computing and sensing technologies, Internet of Things (IoT)-based cardiac monitoring plays a crucial role in providing patients with cost-efficient solutions for long-term, continuous, and pervasive electrocardiogram (ECG) monitoring outside a hospital setting. In a typical IoT-based ECG monitoring system, ECG signals are picked up by sensors located on the edge, and then uploaded to the remote cloud servers. ECG interpretation is performed for the collected ECGs in the cloud servers and the analysis results can be made instantly available to the patients as well as their healthcare providers.In this dissertation, we first examine the …

Healthcare Facilities: Maintaining Accessibility While Implementing Security, Ryan Vilter

UNO Student Research and Creative Activity Fair

In the wake of the Tulsa, Oklahoma hospital shooting in the summer of 2022, it was made clear that more security needed to be implemented in healthcare facilities. As a result, I inquired: What is the happy balance for healthcare facilities to maintain their accessibility to the public while also implementing security measures to prevent terrorist attacks? With that base, I give recommendations in the areas of cybersecurity, physical infrastructure, and physical and mental health, based off the existing literature and data gathered from terrorist attacks against hospitals over several decades.

A Scoping Review Of Digital Health Interventions For Combating Covid-19 Misinformation And Disinformation, Katarzyna Czerniak, Raji Pillai, Abhi Parmar, Kavita Ramnath, Joseph Krocker, Sahiti Myneni

Faculty, Staff and Student Publications

OBJECTIVE: We provide a scoping review of Digital Health Interventions (DHIs) that mitigate COVID-19 misinformation and disinformation seeding and spread.

MATERIALS AND METHODS: We applied our search protocol to PubMed, PsychINFO, and Web of Science to screen 1666 articles. The 17 articles included in this paper are experimental and interventional studies that developed and tested public consumer-facing DHIs. We examined these DHIs to understand digital features, incorporation of theory, the role of healthcare professionals, end-user experience, and implementation issues.

RESULTS: The majority of studies (n = 11) used social media in DHIs, but there was a lack of platform-agnostic generalizability. …

Intellectual Disability Related To De Novo Germline Loss Of The Distal End Of The P-Arm Of Chromosome 17: A Case Report, Eden Pope, Matthew Huertas, Amar Paul, Braden Cunningham, Matthew Jennings, Ryan Perry, Stephanie Chavez, John A. Kriak, Kyle B. Bills, David W. Sant

Annual Research Symposium

Hypothesis/Purpose: In this report we present a case of a 20-year-old female with congenital intellectual disability, stunted growth, and hypothyroidism. Competitive genetic hybridization (CHG) revealed a loss of 17p13.3, and the deletion was not present in either parent. This deletion has not previously been characterized, but mutations on the p-arm of chromosome 17 are responsible for Miller-Dieker Syndrome and Isolated Lissencephaly Sequence, both of which share symptoms in common with the patient.

Methods: Peripheral mononuclear cells (PBMCs) were used for karyotyping and competitive genetic hybridization (CHG). Bioinformatic analysis was carried out using the Genome Data Viewer (ncbi.nlm.nih.gov/genome/gdv).

Results: Karyotype was …

Investigating Respiratory Simplification Caused By Prenatal Rage Upregulation, Paul Reynolds

Annual Research Symposium

No abstract provided.

Potential Role For Rage In The Development Of Secondhand Smoke-Induced Chronic Sinusitis, Paul Reynolds

Annual Research Symposium

No abstract provided.

Rage Inhibition Reduces Timp And Decreases Cell Invasion In Cigarette Smoke Extract (Cse) Treated Oral Squamous Carcinoma Cells, Paul Reynolds

Annual Research Symposium

No abstract provided.

Inflammatory Cytokine Elaboration Following Secondhand Smoke Exposure Is Mediated In Part By Rage Signaling, Paul Reynolds

Annual Research Symposium

No abstract provided.

Rage Availability Lessens The Degree Of Dysfunctional Mitochondrial Bioenergetics Following Chronic Secondhand Smoke Exposure, Paul Reynolds

Annual Research Symposium

No abstract provided.

Gestational Dependent Responses To Second Hand Smoke (Shs) In Mouse Pregnancies, Paul Reynolds

Annual Research Symposium

No abstract provided.

Reversible Emerging Neuropsychological Pattern In Chronic Intractable Migraine, Tanner Williford, Pooja Chemiti, Mason Allen, Brandon Burrell, Stephanie Chavez, Jude Emego, Bridger Gunter, Matthew Huertas, Matthew Jennings, Roshni Jogin, Paulo Kelly, Laura Minor, Steven Salazar, Jameson Williams, David W. Sant, John A. Kriak, Kyle B. Bills

Annual Research Symposium

No abstract provided.

The Immunomodulating Effects Of Morphine Dependence And Withdrawal In Rat Lung, Liver, Spleen And Blood, Yensi Munoz

Annual Research Symposium

No abstract provided.

The Current State Of Underrepresented Osteopathic Minorities In Competitive Specialties, Emmanuel Oyalabu, Steve Guzman, Dashon Eure, Ezenna Obilor

Annual Research Symposium

It is well documented that barriers exist for underrepresented minorities to enter the field of medicine and even more competitive residencies. As defined by the NRMP, competitive specialties include but are not limited to Interventional Radiology, Orthopedic Surgery, Plastic Surgery, Radiation Oncology, Vascular Surgery, Neurosurgery, Dermatology, and Otornylogy (NRMP-AMA). A large number of osteopathic medical school graduates have a history of going into primary care specialties because many osteopathic medical schools have a primary care focus (Primary Care- Osteopathic Medicine). The emphasis on primary care, whether intentional or not, can foster a less-than-advantageous environment for underrepresented minority students (URM), pursuing …

Appearance Of Two Distinct Clusters Of Glucose Dysregulation In Chronic Intractable Migraine, Roshni Jogin, Kaitlyn Mcfarland, Aparna Naik, Tanner Williford, Matthew Conway, Amar Paul, John A. Kriak, David W. Sant, Kyle B. Bills

Annual Research Symposium

No abstract provided.

Planning A Review Of The Pathogenesis And Management Of Valley Fever, Seattle Shakur

Annual Research Symposium

No abstract provided.

Clinical Trial Subject Recruitment: Research Immersion Experience, Brooklyn Janes

Annual Research Symposium

No abstract provided.

Sulopenem For The Treatment Of Complicated And Uncomplicated Bacterial Urinary Tract Infection (Uti), Aiyi Chen, Thanh-Liem Vu, Daniel J. Yang, Landon Olsen

Annual Research Symposium

No abstract provided.

Focus Group Interview Experience Of A University Clinical Research Team, Kade Janes

Annual Research Symposium

No abstract provided.

Development Of A Census Driven Equation To Predict Non-Billable "Cross-Cover" Work Done During Nocturnist Shifts To Predict Staffing, Bibhash Neupane

Annual Research Symposium

No abstract provided.