Open Access. Powered by Scholars. Published by Universities.®
Other Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Optimization (3)
- Health services (2)
- Simulation (2)
- Aerospace manufacturing (1)
- Air handling unit (1)
-
- Appointment scheduling (1)
- Artificial Intelligence (1)
- Binomial Probability (1)
- Chronic Kidney Disease (CKD); Acute Kidney Injury (AKI); Clustering; Machine Learning (1)
- Clean air (1)
- Clinical Supply (1)
- Clinical Trials (1)
- Collaboration (1)
- Computational efficiency (1)
- Conditional logistic regression (1)
- Covid-19 (1)
- Data collection (1)
- Data modeling (1)
- Data visualization (1)
- Decision making (1)
- Decision support (1)
- Decontaminate air (1)
- Decontamination (1)
- Design engineering (1)
- Discrete choice experiment (1)
- Drug Development (1)
- Ducts and vents (1)
- Emergency Medicine (1)
- Explosions (1)
- Fatalities (1)
- Publication
-
- Masters Theses (3)
- Theses and Dissertations (3)
- Doctoral Dissertations (2)
- All Dissertations (1)
- Articles (1)
-
- Community & Environmental Health Faculty Publications (1)
- Department of Industrial and Management Systems Engineering: Faculty Publications (1)
- Graduate Theses, Dissertations, and Problem Reports (1)
- Industrial Engineering Undergraduate Honors Theses (1)
- Night Flight Journal (1)
- Publications and Research (1)
- Publication Type
- File Type
Articles 1 - 16 of 16
Full-Text Articles in Other Operations Research, Systems Engineering and Industrial Engineering
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
Masters Theses
One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …
Improving Patient Safety, Patient Flow And Physician Well-Being In Emergency Departments, Vishnunarayan Girishan Prabhu
Improving Patient Safety, Patient Flow And Physician Well-Being In Emergency Departments, Vishnunarayan Girishan Prabhu
All Dissertations
Over 151 million people visit US Emergency Departments (EDs) annually. The diverse nature and overwhelming volume of patient visits make the ED one of the most complicated settings in healthcare to study. ED overcrowding is a recognized worldwide public health problem, and its negative impacts include patient safety concerns, increased patient length of stay, medical errors, patients left without being seen, ambulance diversions, and increased health system expenditure. Additionally, ED crowding has been identified as a leading contributor to patient morbidity and mortality. Furthermore, this chaotic working environment affects the well-being of all ED staff through increased frustration, workload, stress, …
Evaluating The Military Medical Evacuation Dispatching And Delivery Problem Via Simulation And Self-Exciting Hawkes Process, Virbon B. Frial
Evaluating The Military Medical Evacuation Dispatching And Delivery Problem Via Simulation And Self-Exciting Hawkes Process, Virbon B. Frial
Theses and Dissertations
The location, allocation, and utilization of military medical evacuation (MEDEVAC) resources significantly impact the quality and timeliness of medical care to injured troops. In 2009, Secretary of Defense Robert Gates introduced the Golden Hour mandate that entails the evacuation of critically-injured troops to military treatment facilities (MTFs) within an hour to prevent further complications. To develop high-quality policies that improve MEDEVAC system performance, several papers in the current literature assume that MTFs have both the capacity and capability of treating any patient, regardless of the type of injury. However, these assumptions are unrealistic when conducting high-intensity operations. While acknowledging MTF …
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Articles
Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …
Developing Artificial Intelligence Tools To Investigate The Phenotypes And Correlates Of Chronic Kidney Disease Patients In West Virginia, Marzieh Amiri Shahbazi
Developing Artificial Intelligence Tools To Investigate The Phenotypes And Correlates Of Chronic Kidney Disease Patients In West Virginia, Marzieh Amiri Shahbazi
Graduate Theses, Dissertations, and Problem Reports
ABSTRACT
Developing Artificial Intelligence tools to investigate the phenotypes and correlates of Chronic Kidney Disease patients in West Virginia
Marzieh Amiri Shahbazi
Chronic kidney disease (CKD) is responsible for disrupting the lives of 37 million people just in the USA, which is about 1 in 7 adults. CKD results in a gradual loss of kidney function over time. Sometimes CKD doesn’t produce any significant symptoms until it reaches an advanced stage. On the other hand, acute kidney injury (AKI) accounts for a sudden decline in the kidney’s function. As a result, the kidneys fail to filter waste materials from the …
The Probability Of Success-Through Fault Tree Analytical Binomial Result, Tyleka Riddle
The Probability Of Success-Through Fault Tree Analytical Binomial Result, Tyleka Riddle
Night Flight Journal
Prestigious Appeal Rule of Thumb (Ear Drum Plugs)
In truant fashion, with proven accidental probabilistic perception for proposed cued facial expression recognition and voice commands without filtering. The estimated cost analysis for design and development generated from the enhanced project in the word "no”: Additionally, an audio noise effect size (ES) for desired level of comprehensive sensory receptors in sound reference to noisy party syndrome. Sytoss, (2019) "Resulting in a cocktail party theory for chalkboard distinction and conversation with applied facial recognition. As well as, the enhanced project management tool, EPMT, to provide output and input determination for higher-level acoustic …
Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environment - Part 2: Approaches To Mitigation, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore
Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environment - Part 2: Approaches To Mitigation, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore
Publications and Research
The challenge we face in implementing solutions for new HVAC ventilation and filtration design, is to effectively improve air quality for virus mitigation without losing performance efficiency. The purpose of this improvement is to decontaminate the occupied enclosed areas, reducing the transmission of the corona virus aerosol transmission. Our research seeks reliable approaches to mitigate the further spread of aerosol transmission in indoor spaces. The methodology is to examine innovative HVAC engineering solutions that combat epidemiological problems of Covid-19 for the post-pandemic era, by researching scholarly articles and ASHRAE journals. We are achieving the goal of finding highly efficient resolutions …
Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee
Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee
Community & Environmental Health Faculty Publications
Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …
Preferred Treatment Methods For Patients With Inflammatory Bowel Disease, James L. Deitschel
Preferred Treatment Methods For Patients With Inflammatory Bowel Disease, James L. Deitschel
Theses and Dissertations
Shared decision making is the concept of physicians involving patients in the treatment planning process. The University of Maryland Medical Center is interested in applying shared decision making to the treatment of patients with Inflammatory Bowel Disease (IBD). The two treatment methods analyzed in this study were medical management and surgery. To explore patient preferences between these two alternatives, a discrete choice experiment (DCE) was employed. The responses for the DCE were binary, so logistic regression models were explored. The conditional logistic regression model was determined to be the most appropriate for this analysis. After step-wise regression was performed, a …
Three Essays On Data-Driven Optimization For Scheduling In Manufacturing And Healthcare, Ekin Koker
Three Essays On Data-Driven Optimization For Scheduling In Manufacturing And Healthcare, Ekin Koker
Doctoral Dissertations
This dissertation consists of three essays on data-driven optimization for scheduling in manufacturing and healthcare. In Chapter 1, we briefly introduce the optimization problems tackled in these essays. The first of these essays deals with machine scheduling problems. In Chapter 2, we compare the effectiveness of direct positional variables against relative positional variables computationally in a variety of machine scheduling problems and we present our results. The second essay deals with a scheduling problem in healthcare: the team primary care practice. In Chapter 3, we build upon the two-stage stochastic integer programming model introduced by Alvarez Oh (2015) to solve …
A Computational Simulation Model For Predicting Infectious Disease Spread Using The Evolving Contact Network Algorithm, Buyannemekh Munkhbat
A Computational Simulation Model For Predicting Infectious Disease Spread Using The Evolving Contact Network Algorithm, Buyannemekh Munkhbat
Masters Theses
Commonly used simulation models for predicting outbreaks of re-emerging infectious diseases (EIDs) take an individual-level or a population-level approach to modeling contact dynamics. These approaches are a trade-off between the ability to incorporate individual-level dynamics and computational efficiency. Agent-based network models (ABNM) use an individual-level approach by simulating the entire population and its contact structure, which increases the ability of adding detailed individual-level characteristics. However, as this method is computationally expensive, ABNMs use scaled-down versions of the full population, which are unsuitable for low prevalence diseases as the number of infected cases would become negligible during scaling-down. Compartmental models use …
Data Visualization Of Treatment Outcomes For Tuberculosis Patients, Joy Jenkins
Data Visualization Of Treatment Outcomes For Tuberculosis Patients, Joy Jenkins
Industrial Engineering Undergraduate Honors Theses
Tuberculosis is an infectious disease, and different treatments have been discovered over the years. However, patients may develop various drug resistance levels that affect the likelihood of becoming cured or dying. In this study, we sought to employ data visualization to explore the relationship between treatment trajectory, as indicated by smear and culture results in the follow-up tests and patient outcomes. A large sample of patients have been broken down by demographics including age, gender, and drug resistance status. Sankey diagrams were used to visualize the pathway progression of the patients over time split between two time periods- months 0-6 …
Simulation Of 48-Hour Queue Dynamics For A Semi-Private Hospital Ward Considering Blocked Beds, Wei Chen
Simulation Of 48-Hour Queue Dynamics For A Semi-Private Hospital Ward Considering Blocked Beds, Wei Chen
Masters Theses
This thesis study evaluates access to care at an internal medicine unit with solely semi-private rooms at Baystate Medical Center (BMC). Patients are divided into two types: Type I patient consumes one bed; Type II patient occupies two beds or an entire semi-private room as a private space for clinical reasons, resulting in one empty but unavailable (blocked) bed per Type II patient. Because little data is available on blocked beds and Type II patients, unit-level hospital bed planning studies that consider blocked beds have been lacking. This thesis study bridges that gap by building a single-stream and a two-stream …
Guidelines For Scheduling In Primary Care: An Empirically Driven Mathematical Programming Approach, Hyun Jung Alvarez Oh
Guidelines For Scheduling In Primary Care: An Empirically Driven Mathematical Programming Approach, Hyun Jung Alvarez Oh
Doctoral Dissertations
Primary care practices play a vital role in healthcare delivery since they are the first point of contact for most patients, and provide health prevention, counseling, education, diagnosis and treatment. Practices, however, face a complex appointment scheduling problem because of the variety of patient conditions, the mix of appointment types, the uncertain service times with providers and non-provider staff (nurses/medical assistants), and no-show rates which all compound into a highly variable and unpredictable flow of patients. The end result is an imbalance between provider idle time and patient waiting time. To understand the realities of the scheduling problem we analyze …
Urgent Aeromedical Evacuation Network Capacity Planning, Scott C. Finkbeiner
Urgent Aeromedical Evacuation Network Capacity Planning, Scott C. Finkbeiner
Theses and Dissertations
Aeromedical Evacuation (AE) has been steadily utilized during Operation Iraqi Freedom and Operation Enduring Freedom. AE is a global enterprise. The current structure of AE is facing changes as forces scale down from operations in Iraq and Afghanistan. AE will, however, continue to be important in its domestic use in the continental USA (CONUS). Current practice is to pull aircraft (e.g. C-17, C-130 or KC-135) from their normal operations to meet Urgent and Priority patient needs when local alternatives are infeasible. An alternative to the current system would be having a centralized "bed-down" location for AE operations that would house …
Selecting For Random Drug Testing At Union Pacific Railroad, Jennifer Meyer, Paul Savory
Selecting For Random Drug Testing At Union Pacific Railroad, Jennifer Meyer, Paul Savory
Department of Industrial and Management Systems Engineering: Faculty Publications
Many industries have recently implemented programs to detect and deter the use of recreational drugs in the workplace. The transportation industry has received careful government attention, particularly where the safety of the public may be seriously affected by employees who use drugs. Following federal guidelines, Union Pacific Railroad first implemented a random drug-testing plan in 1990. Because the assigned jobs, shifts, and work locations of many railroad employees change frequently, defining the selection population was particularly challenging. In its continuing efforts to validate and improve this plan, Union Pacific Railroad sought an external evaluation to determine the fairness of its …