Computer Sciences Commons^™

Visualizing The Opioid Overdose With A Dynamic Heat Map To Identify And Predict Vulnerable Communities, Justin R. Chang, Garrett K. Wong, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow

Graduate Research Posters

Background: Opioid and heroin overdose epidemic is a public health emergency in the state of Virginia. In order to prevent overdose deaths, we need the target expertise in substance use disorders to areas with high rates of overdose. In particular, an area with an acute spike in overdoses might represent an urgent need for intervention.

Aims: The CDC urges the use of near real-time surveillance to effectively identify overdose incidence, and to coordinate community responses in the states affected by the epidemic, including Virginia. However, current opioid overdose datasets for Virginia lack adequate consistency, granularity, and temporality for …

The Efficacy Of An Emr-Enabled Text Messaging System To The Expanded Health Beliefs, Diabetes Care Profile And Hba1c Of Diabetes Mellitus Patients, Ma. Regina Justina E. Estuar, John Noel Victorino, Razel Custodio

Department of Information Systems & Computer Science Faculty Publications

As diabetes mellitus (DM) becomes a global emergency, there is a need to explore novel interventions to address problems in self – management. Literature agree in the potential of mobile phones to carry-out self-care for a wide-array of disease conditions. Diabetes Self – Management Support and Education Through Text – Messaging (DSMSET) is a low-cost, two-way text messaging system designed to deliver self - help, educational messages based on the nine (9) dimensions of health management. DSMSET serves as a plugin to SHINE OS+, an open – source electronic medical record (EMR) system. The research is also based on the …

Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for hybrid privacy-preserving clinical decision support system in fog cloud computing, called HPCS. In HPCS, a fog server uses a lightweight data mining method to securely monitor patients' health condition in real-time. The newly detected abnormal symptoms can be further sent to the cloud server for high-accuracy prediction in a privacy-preserving way. Specifically, for the fog servers, we design a new secure outsourced inner-product protocol for achieving secure lightweight single-layer neural network. Also, a privacy-preserving piecewise polynomial calculation protocol allows cloud server to securely perform any activation functions in multiple-layer neural network. Moreover, …

Deep Convolutional Neural Networks Enable Discrimination Of Heterogeneous Digital Pathology Images, Pegah Khosravi, Ehsan Kazemi, Marcin Imielinski, Olivier Elemento, Iman Hajirasouliha

Publications and Research

Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and automated image analysis approaches have great potential to increase precision of diagnosis and help reduce human error.

In this study, we utilize several computational methods based on convolutional neural networks (CNN) and build a stand-alone pipeline to effectively classify different histopathology images across different types of cancer.

In particular, we demonstrate the utility of our pipeline to discriminate between two subtypes of lung cancer, four biomarkers of bladder cancer, and five biomarkers of breast cancer. In addition, we apply our pipeline to discriminate among four immunohistochemistry …

Technology Acceptance And Compliance In Obstructive Sleep Apnea Patients, Asif Kidwai

Walden Dissertations and Doctoral Studies

The focus of this study is the problem of declining trend in obstructive sleep apnea (OSA) patient compliance. Studies reported improved compliance in patients with chronic diseases due to technology-based interventions. However, researchers have not investigated the advantages of technology to improve the compliance of OSA patients in detail. The specific problem was the lack of engagement between patients and healthcare managers, resulting in low compliance within OSA patients. The purpose of this qualitative study was to evaluate how technology-based interventions can improve OSA patient engagement with the healthcare managers resulting in improved compliance with treatment procedures. In this study, …

Leveraging Artificial Intelligence To Improve Provider Documentation In Patient Medical Records, Evangeline C. Ozurigbo

Walden Dissertations and Doctoral Studies

Clinical documentation is at the center of a patient's medical record; this record contains all the information applicable to the care a patient receives in the hospital. The practice problem addressed in this project was the lack of clear, consistent, accurate, and complete patient medical records in a pediatric hospital. Although the occurrence of incomplete medical records has been a known issue for the project hospital, the issue was further intensified following the implementation of the 10th revision of International Classification of Diseases (ICD-10) standard for documentation, which resulted in gaps in provider documentation that needed to be filled. Based …

Staff Education Module For Bar Code Medication Administration, Francoise Juste

Walden Dissertations and Doctoral Studies

Bar Code Medication Administration (BCMA) is a technology-supported nursing tool that has become the standard of practice for medication administration. When used effectively and efficiently, this tool has the potential to reduce medication errors in acute care settings. In a pediatric unit at a major urban hospital in the northeast region of the United States, the absence of a BCMA nursing staff educational module affected the use of this safety tool leading to an increase of medication errors. The purpose of this DNP project was to develop a comprehensive educational module to promote BCMA in the pediatric unit of the …

Public Health Providers' Perceptions Of Electronic Health Records In A Disaster, Sherhonda Yvette Harper

Walden Dissertations and Doctoral Studies

The introduction of federal initiatives and incentives regarding health information technology fostered a movement towards the adoption of electronic health records (EHR). Implementation of EHRs sparked discussions among healthcare providers, patients, and others about the benefits or challenges of the move from the traditional paper method to the electronic version in healthcare settings. A knowledge gap in research involving the usefulness of EHRs and their impact to the delivery of care in other settings exists. The purpose of this qualitative study was to explore public health providers' perceptions of the meaningful use of EHRs in a disaster setting. Study participants …

Strategies For Applying Electronic Health Records To Achieve Cost Saving Benefits, Daniel Kanyi Ngunyu

Walden Dissertations and Doctoral Studies

The American Recovery and Reinvestment Act (ARRA) of 2009 authorized the distribution of about $30 billion incentive funds to accelerate electronic health record (EHR) applications to improve the quality of care, safety, privacy, care coordination, and patients' involvement in healthcare. EHR use has the potential of saving $731 in costs for hospitals per patient admission; however, most hospitals are not applying EHR to reach the level at which cost savings are possible. The purpose of this single case study was to explore strategies that IT leaders in hospitals can use to apply EHR to achieve the cost saving benefits. The …

Minimally Actuated Walking: Identifying Core Challenges To Economical Legged Locomotion Reveals Novel Solutions, Ryan T. Schroeder, John Ea Bertram

Research outputs 2014 to 2021

Terrestrial organisms adept at locomotion employ strut-like legs for economical and robust movement across the substrate. Although it is relatively easy to observe and analyze details of the solutions these organic systems have arrived at, it is not as easy to identify the problems these movement strategies have solved. As such, it is useful to investigate fundamental challenges that effective legged locomotion overcomes in order to understand why the mechanisms employed by biological systems provide viable solutions to these challenges. Such insight can inform the design and development of legged robots that may eventually match or exceed animal performance. In …

Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang

Theses and Dissertations

Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.

With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …

A Framework For Development Of Android Mobile Electronic Prescription Transfer Applications In Compliance With Security Requirements Mandated By The Australian Healthcare Industry, Kyaw Kyaw Htat

Theses: Doctorates and Masters

This thesis investigates mobile electronic transfer of prescription (ETP) in compliance with the security requirements mandated by the Australian healthcare industry and proposes a framework for the development of an Android mobile electronic prescription transfer application. Furthermore, and based upon the findings and knowledge from constructing this framework, another framework is also derived for assessing Android mobile ETP applications for their security compliance.

The centralised exchange model-based ETP solution currently used in the Australian healthcare industry is an expensive solution for on-going use. With challenges such as an aging population and the rising burden of chronic disease, the cost of …

A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui

Research Collection School Of Computing and Information Systems

Electronic Health Record (EHR) is a digital health documentary. It contains not only the health-related records but also the personal sensitive information. Therefore, how to reliably share EHR through the cloud is a challenging issue. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography prototype, which can achieve fine-grained access control as well as one-to-many encryption. In CP-ABE, access policy is attached to the ciphertext, and however, the access policy is not protected, which will also cause some privacy leakage. In this paper, we propose a policy preserving EHR system on the basis of CP-ABE. Specifically, we designed an algorithm, which …

Atomistic Simulations And Network-Based Modeling Of The Hsp90-Cdc37 Chaperone Binding With Cdk4 Client Protein: A Mechanism Of Chaperoning Kinase Clients By Exploiting Weak Spots Of Intrinsically Dynamic Kinase Domains, John Czemeres, Kurt Buse, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

A fundamental role of the Hsp90 and Cdc37 chaperones in mediating conformational development and activation of diverse protein kinase clients is essential in signal transduction. There has been increasing evidence that the Hsp90-Cdc37 system executes its chaperoning duties by recognizing conformational instability of kinase clients and modulating their folding landscapes. The recent cryo-electron microscopy structure of the Hsp90-Cdc37- Cdk4 kinase complex has provided a framework for dissecting regulatory principles underlying differentiation and recruitment of protein kinase clients to the chaperone machinery. In this work, we have combined atomistic simulations with protein stability and network-based rigidity decomposition analyses to characterize dynamic …

Virtual Reality As A Training Tool To Treat Physical Inactivity In Children, Adam W. Kiefer, David Pincus, Michael J. Richardson, Gregory D. Myer

Psychology Faculty Articles and Research

Lack of adequate physical activity in children is an epidemic that can result in obesity and other poor health outcomes across the lifespan. Physical activity interventions focused on motor skill competence continue to be developed, but some interventions, such as neuromuscular training (NMT), may be limited in how early they can be implemented due to dependence on the child’s level of cognitive and perceptual-motor development. Early implementation of motor-rich activities that support motor skill development in children is critical for the development of healthy levels of physical activity that carry through into adulthood. Virtual reality (VR) training may be beneficial …

The Ability Of Different Imputation Methods To Preserve The Significant Genes And Pathways In Cancer, Rosa Aghdam, Taban Baghfalaki, Pegah Khosravi, Elnaz Saberi Ansari

Publications and Research

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase …

An Analysis Of Operant Conditioning And Its Relationship With Video Game Addiction, Daniel Vu

ART 108: Introduction to Games Studies

A report published by the Entertainment Software Association revealed that in 2015, 155 million Americans play video games with an average of two gamers in each game-playing household (Entertainment Software Association, “Essential Facts about the Computer and Video Game Industry”). With this massive popularity that has sprung alongside video games, the question must be asked: how are video games affecting today's people? With the current way some video games are structured, the video game rewards players for achieving certain accomplishments. For example, competitive video games reward players who achieve victories by giving them a higher ranking or other games display …

Canines For Disabled Kids, Erin Jerrett, Margarita Mnatsakanyan, Colleen Reynolds, Yin Wang

School of Professional Studies

Canines for Disabled Kids have been working on behalf of children and their families to educate communities and promote service dog partnerships for almost twenty years. Their advocacy with local legislatures, business owners, and community leaders highlighted the difficulties encountered when differentiating service dogs from emotional support/comfort dogs. Service dogs are entitled to access by the Americans with Disabilities Act (ADA), while emotional support/comfort dogs are not protected under the federal statute or to the same rights. Canines for Disabled Kids proposed a study to obtain a current count of licensed service dogs in the Commonwealth and investigate the feasibility …

A Cluster Analysis Of Challenging Behaviors In Autism Spectrum Disorder, Elizabeth Stevens, Abigail Atchison, Laura Stevens, Esther Hong, Doreen Granpeesheh, Dennis Dixon, Erik J. Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

We apply cluster analysis to a sample of 2,116 children with Autism Spectrum Disorder in order to identify patterns of challenging behaviors observed in home and centerbased clinical settings. The largest study of this type to date, and the first to employ machine learning, our results indicate that while the presence of multiple challenging behaviors is common, in most cases a dominant behavior emerges. Furthermore, the trend is also observed when we train our cluster models on the male and female samples separately. This work provides a basis for future studies to understand the relationship of challenging behavior profiles to …

Using Virtual Reality To Improve Sitting Balance, Alice Kay Barnes

Graduate Theses/Dissertations

This thesis focuses on using virtual reality (VR) to enhance sitting balance and core strength. It is a study in how to create a VR exercise program which is interesting enough to keep players/patients motivated, but comfortable to play and not overwhelming to the senses. The software used for this study was written with the hope that a later version of it might be used with occupational/physical therapy patients one day. For this master’s thesis, the initial testing has been done with healthy volunteers. The software incorporates what developers know thus far about designing for VR, and it is hoped …

Altering The Expression Of Artemisinin Through Osmotic Manipulation, Tyler Friesen

Theses/Capstones/Creative Projects

Artemisinin is an anti-malarial drug used in combination therapy to treat all malarial parasites in the blood stage. The expression of artemisinin within the plant Artemisia annua is only 1% of the dry weight. Methods for increasing the level of artemisinin within the plant were proposed. This paper looks into finding homologous enzymes across multiple species in order to find species where genetic manipulations will be useful. The second part of this paper looks at the use of osmotic stress to increase the reactive oxygen species in order to increase the amount of artemisinin within the plant. The database portion …

Disease Gene Classification With Metagraph Representations, Sezin Kircali Ata, Yuan Fang, Min Wu, Xiao-Li Li, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes. As disease proteins tend to have a similar topological characteristics …

Home Health Care Delivery Problem, Aldy Gunawan, Hoong Chuin Lau, Kun Lu

Research Collection School Of Computing and Information Systems

We address the Home Health Care Delivery Problem (HHCDP), which is concerned with staff scheduling in the home health care industry. The goal is to schedule health care providers to serve patients at their homes that maximizes the total collected preference scores from visited patients subject to several constraints, such as workload of the health care providers, time budget for each provider and so on. The complexity lies in the possibility of cancellation of patient bookings dynamically, and the generated schedule should attempt to patients’ preferred time windows. To cater to these requirements, we model the preference score as a …

Using Data To Improve Services For Infants With Hearing Loss: Linking Newborn Hearing Screening Records With Early Intervention Records, Maria Gonzalez, Lori Iarossi, Yan Wu, Ying Huang, Kirsten Siegenthaler

Journal of Early Hearing Detection and Intervention

The purpose of this study was to match records of infants with permanent hearing loss from the New York Early Hearing Detection and Intervention Information System (NYEHDI-IS) to records of infants with permanent hearing loss receiving early intervention services from the New York State Early Intervention Program (NYSEIP) to identify areas in the state where hearing screening, diagnostic evaluations and referrals to the NYSEIP were not being made or documented in a timely manner. Data from 2014-2016 NYEHDI-IS and NYEIS information systems were matched using The Link King. There were 274 infants documented in NYEIS Information System as receiving early …

Context-Based Human Activity Recognition Using Multimodal Wearable Sensors, Pratool Bharti

USF Tampa Graduate Theses and Dissertations

In the past decade, Human Activity Recognition (HAR) has been an important part of the regular day to day life of many people. Activity recognition has wide applications in the field of health care, remote monitoring of elders, sports, biometric authentication, e-commerce and more. Each HAR application needs a unique approach to provide solutions driven by the context of the problem. In this dissertation, we are primarily discussing two application of HAR in different contexts. First, we design a novel approach for in-home, fine-grained activity recognition using multimodal wearable sensors on multiple body positions, along with very small Bluetooth beacons …

Ordinal Convolutional Neural Networks For Predicting Rdoc Positive Valence Psychiatric Symptom Severity Scores, Anthony Rios, Ramakanth Kavuluru

Computer Science Faculty Publications

Background—The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task.

Objective—Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification. In this effort, we study ordinal regression problems with text data where misclassifications are penalized differently based on how far apart the ground truth and model predictions are …

Predicting Mental Conditions Based On "History Of Present Illness" In Psychiatric Notes With Deep Neural Networks, Tung Tran, Ramakanth Kavuluru

Computer Science Faculty Publications

Background—Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenario by providing the first set of neuropsychiatric notes to participants. This study summarizes our efforts and results in proposing a novel data use case for this dataset as part of the third track in this shared task.

Objective—We explore the feasibility and effectiveness of predicting a set of common mental conditions a patient has based on the short textual description of patient’s history …

Phosphoproteomics Profiling Of Nonsmall Cell Lung Cancer Cells Treated With A Novel Phosphatase Activator, Danica Wiredja, Marzieh Ayati, Sahar Mazhar, Jaya Sangodkar, Sean Maxwell, Daniela Schlatzer, Goutham Narla, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications

Activation of protein phosphatase 2A (PP2A) is a promising anti-cancer therapeutic strategy, as this tumor suppressor has the ability to coordinately downregulate multiple pathways involved in the regulation of cellular growth and proliferation. In order to understand the systems-level perturbations mediated by PP2A activation, we carried out mass spectrometry-based phosphoproteomic analysis of two KRAS mutated non-small cell lung cancer (NSCLC) cell lines (A549 and H358) treated with a novel Small Molecule Activator of PP2A (SMAP). Overall, this permitted quantification of differential signaling across over 1,600 phosphoproteins and 3,000 phosphosites. Kinase activity assessment and pathway enrichment implicated collective downregulation of RAS …

Structure-Based Drug Discovery: Computational Virtual Screening, Robert C. Monsen, Lynn Deleeuw, Jon Maguire, William L. Dean, Robert D. Gray, Jonathan B. Chaires, John O. Trent

Commonwealth Computational Summit

No abstract provided.

Parallelization Of A Three-Dimensional Full Multigrid Algorithm To Simulate Tumor Growth, Dylan Goodin, Chin F. Ng, Hermann B. Frieboes

Commonwealth Computational Summit

We present the performance gains of an openMP implementation of a fully adaptive nonlinear full multigrid (FMG) algorithm to simulate three-dimensional multispecies desmoplastic tumor growth on computer systems of varying processing capabilities. The FMG algorithm is applied to solve a recently published thermodynamic mixture model that uses a diffuse interface approach with fourth-order reaction-advection-diffusion PDEs (Cahn-Hilliard-type equations) that are coupled, nonlinear, and numerically stiff. The model includes multiple cell species and extracellular matrix (ECM), with adhesive and elastic energy contributions in chemical potential terms, as well as including blood and lymphatic vessels represented as continuous vasculatures. Advection-reaction-diffusion PDEs are employed …