Computer Sciences Commons^™

Multiple Sclerosis Identification Based On Fractional Fourier Entropy And A Modified Jaya Algorithm, Shui-Hua Wang, Hong Cheng, Preetha Phillips, Yu-Dong Zhang

Publications and Research

Aim: Currently, identifying multiple sclerosis (MS) by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to identify MS in an automatic way. This proposed method first extracted the fractional Fourier entropy map from a specified brain image. Afterwards, it sent the features to a multilayer perceptron trained by a proposed improved parameter-free Jaya algorithm. We used cost-sensitivity learning to handle the imbalanced data problem. Results: The 10 × 10-fold cross validation showed our method yielded a sensitivity of 97.40 ± 0.60%, …

Cross-Platform Openhds Web Application, Nick Littlefield

Thinking Matters Symposium Archive

A proof of concept cross platform data collection application for Demographic and Health studies has been developed. This application allows for the collection of information about locations, individuals, births, and deaths within a region. This application can be run on both mobile devices, laptops, and desktops.

Similarity Based Classification Of Adhd Using Singular Value Decomposition, Taban Eslami, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Attention deficit hyperactivity disorder (ADHD) is one of the most common brain disorders among children. This disorder is considered as a big threat for public health and causes attention, focus and organizing difficulties for children and even adults. Since the cause of ADHD is not known yet, data mining algorithms are being used to help discover patterns which discriminate healthy from ADHD subjects. Numerous efforts are underway with the goal of developing classification tools for ADHD diagnosis based on functional and structural magnetic resonance imaging data of the brain. In this paper, we used Eros, which is a technique for …

Compressed Sensing For Few-View Multi-Pinhole Spect With Applications To Preclinical Imaging, Benjamin Michael Rizzo

Dissertations (1934 -)

Single Photon Emission Computed Tomography (SPECT) can be used to identify and quantify changes in molecular and cellular targets involved in disease. A radiopharmaceutical that targets a specific metabolic function is administered to a subject and planar projections are formed by imaging emissions at different view angles around the subject. The reconstruction task is to determine the distribution of radioactivity within the subject from the projections. We present a reconstruction approach that utilizes only a few view angles, resulting in a highly underdetermined system, which could be used for dynamic imaging applications designed to quantify physiologic processes altered with disease. …

Foundations Of Health Information Technology (Undergraduate) Course Materials, Chi Zhang

Computer Science and Information Technology Ancillary Materials

This is a collection of all materials used in Health Information Technology by Dr. Chi Zhang at Kennesaw State University, including lecture slides, assignments, and assessments, including a question bank.

Topics covered include:

• Clinical Financial Records
• Evidence-Based Medicine
• e-Prescribing
• Patient Bedside Systems
• Telemedicine
• Health Information Networks
• Cryptography
• Accreditation
• HIPAA Privacy and Security

Volume 10, Taylor Hogg, Tiffany Carter, Brandyn Johnson, Haleigh James, Josh Baker, Tyler Cernak, Kirsten Bauer, Allie Snavely, Mary Zell Galen, Eric Powell, Thomas Wise, Katie Kinsey, Beth Barbolla, Maeleigh Ferlet, Rebecca Morra, Michala Day, Alexandra Evangelista, Max Flores, Harley Hodges, Clardene Jones, Harrison Samaniego, Jamesha Watson, Abby Gargiulo, Heather Green, Haley Klepatzki, Juan Guevara, Dani Bondurant, Michael Joseph Link Jr., Pamela Dahl, Maeve Losen, Charlotte Murphey

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Roger A. Byrne

An Analysis of Media Framing in Cases of Violence Against Women by Taylor Hogg

Writing in the Discipline of Nursing by Tiffany Carter

Photography by Brandyn Johnson

The Hidden Life of Beef Cattle: A Study of Cattle Welfare on Traditional Ranches and Industrial Farms by Haleigh James

Bloodworth's by Josh Baker and Tyler Cernak

Prosimians: Little Bodies, Big Significance by Kirsten Bauer

Skinformed by Allie Snavely

Coopertition and Gracious Professionalism: The Effects of First Robotics Folklore and Culture on the Stem Community by Mary Zell Galen

Tilt by Eric Powell And Thomas Wise

The Millennial …

Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek

Research Collection School Of Computing and Information Systems

Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to those of average consumers who tend to be less conscious about health? In this study, we analyze the healthy eating behaviors of active food journalers using data from MyFitnessPal. Surprisingly, our findings show that food journalers do not eat as healthily as they should despite their proclivity to health eating and …

Eat & Tell: A Randomized Trial Of Random-Loss Incentive To Increase Dietary Self-Tracking Compliance, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek, Tianjiao Yun

Research Collection School Of Computing and Information Systems

A growing body of evidence has shown that incorporating behavioral economics principles into the design of financial incentive programs helps improve their cost-effectiveness, promote individuals' short-term engagement, and increase compliance in health behavior interventions. Yet, their effects on long-term engagement have not been fully examined. In study designs where repeated administration of incentives is required to ensure the regularity of behaviors, the effectiveness of subsequent incentives may decrease as a result of the law of diminishing marginal utility. In this paper, we introduce random-loss incentive-a new financial incentive based on loss aversion and unpredictability principles-to address the problem of individuals' …

Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu

Research Collection School Of Computing and Information Systems

A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module …

The Role Of Ehealth In Disasters: A Strategy For Education, Training And Integration In Disaster Medicine, Anthony C. Norris, Jose J. Gonzalez, David T. Parry, Richard E. Scott, Julie Dugdale, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

This paper describes the origins and progress of an international project to advance disaster eHealth (DEH) – the application of eHealth technologies to enhance the delivery of healthcare in disasters. The study to date has focused on two major themes; the role of DEH in facilitating inter-agency communication in disaster situations, and the fundamental need to promote awareness of DEH in the education of disaster managers and health professionals. The paper deals mainly with on-going research on the second of these themes, surveying the current provision of disaster medicine education, the design considerations for a DEH programme for health professionals, …

The Pharmacogene Variation (Pharmvar) Consortium: Incorporation Of The Human Cytochrome P450 (Cyp) Allele Nomenclature Database, Andrea Gaedigk, Magnus Ingelman-Sundberg, Neil A. Miller, J Steven Leeder, Michelle Whirl-Carrillo, Teri E. Klein

Manuscripts, Articles, Book Chapters and Other Papers

The Human Cytochrome P450 (CYP) Allele Nomenclature Database, a critical resource to the pharmacogenetics and genomics communities, will be transitioning to the Pharmacogene Variation (PharmVar) Consortium. In this report we provide a summary of the current database, provide an overview of the PharmVar consortium and highlight the PharmVar database which will serve as the new home for pharmacogene nomenclature.

Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Effective emergency (medical, fire or criminal) response iscrucial for improving safety and security in urban environments. Recent research in improving effectiveness of emergency management systems (EMSs) has utilized data-drivenoptimization models for efficient allocation of emergency response vehicles (ERVs) to base locations. However, thesedata-driven optimization models either ignore the dispatchstrategy of ERVs (typically the nearest available ERV is dispatched to serve an incident) or employ myopic approaches(e.g., greedy approach based on marginal gain). This resultsin allocations that are not synchronised with the real evolution dynamics on the ground or can be improved significantly.To bridge this gap, we make the following contributions: …

Component Tree Analysis Of Cystovirus Φ6 Nucleocapsid Cryo-Em Single Particle Reconstructions, Lucas Oliveira, Ze Ye, Al Katz, Alexandra Alimova, Hui Wei, Gabor T. Herman, Paul Gottlieb

Publications and Research

The 3-dimensional structure of the nucleocapsid (NC) of bacteriophage φ6 is described utilizing component tree analysis, a topological and geometric image descriptor. The component trees are derived from density maps of cryo-electron microscopy single particle reconstructions. Analysis determines position and occupancy of structure elements responsible for RNA packaging and transcription. Occupancy of the hexameric nucleotide triphosphorylase (P4) and RNA polymerase (P2) are found to be essentially complete in the NC. The P8 protein lattice likely fixes P4 and P2 in place during maturation. We propose that the viral procapsid (PC) is a dynamic structural intermediate where the P4 and P2 …

Adverse Event Detection By Integrating Twitter Data And Vaers, Junxiang Wang, Liang Zhao, Yanfang Ye, Yuji Zhang

Faculty & Staff Scholarship

Background: Vaccinehasbeenoneofthemostsuccessfulpublichealthinterventionstodate.However,vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving vaccines. Traditional adverse event reporting systems suffer from several crucial challenges including poor timeliness. This motivates increasing social media-based detection systems, which demonstrate successful capability to capture timely and prevalent disease information. Despite these advantages, social media-based AE detection suffers from serious challenges such as labor-intensive labeling and class imbalance of the training data.

Results: Totacklebothchallengesfromtraditionalreportingsystemsandsocialmedia,weexploittheircomplementary strength and develop a combinatorial classification approach by integrating Twitter data and the Vaccine Adverse Event Reporting System (VAERS) information aiming to identify potential AEs after …

Towards Using A Physio-Cognitive Model In Tutoring For Psychomotor Tasks., Jong W. Kim, Chris Dancy, Robert A. Sottilare

Faculty Conference Papers and Presentations

We report our exploratory research of psychomotor task training in intelligent tutoring systems (ITSs) that are generally limited to tutoring in the desktop learning environment where the learner acquires cognitively oriented knowledge and skills. It is necessary to support computer-guided training in a psychomotor task domain that is beyond the desktop environment. In this study, we seek to extend the current capability of GIFT (Generalized Intelligent Frame-work for Tutoring) to address these psychomotor task training needs. Our ap-proach is to utilize heterogeneous sensor data to identify physical motions through acceleration data from a smartphone and to monitor respiratory activity through …

Graduate Admissions Recruitment Project, Kevin Anderson, Chiemela Dike, Yixin Du, Arvinder Kaur, Amanda Popp, Huizhong Yang

School of Professional Studies

In this project, several comparison schools were interviewed and disclosed to have used search lists to find candidates. The organizations that have valuable search lists which may be of good use for the School of Professional Studies include Educational Testing Service (ETS) and the Graduate Management Admission Council (GMAC). By choosing criteria such as demographics, location, academic performance, educational history provided by search lists, we believe there are many quality candidates for SPS programs. However, as we further investigated the functionality and cost-efficiency or return of investment of GRE search list, we spotted many uncertainties and few solid and successful …

Worcester Center For Crafts: A Transition To Online Sales, Monica Gow, Carly Branconnier, Srilatha Prodduturi, Ekaterina Shusharina, Alberta Yamoah

School of Professional Studies

The Clark University School of Professional Studies created a capstone team consisting of Monica Gow, Carly Branconnier, Iana Matkovskaia, Srilatha Prodduturi, Ekaterina Shusharina, and Alberta Yamoah to assist Worcester Center for Crafts (WCC) with the launch of their new online store. Worcester Center for Crafts wanted to showcase their beautiful American handmade crafts on an online platform, Shopify, in order to increase their sales and expand their market reach. The capstone team created a charter that outlined the scope of the project and what the team would deliver to WCC by the end of the project. The team agreed to …

Audubon Data Project Final Report, Askhat Beygenov, Valinur Kutlambetov, Shrikant Patel, Phoebe Roberts, Ulfat Sayyed, Shriram Sivaraman

School of Professional Studies

The Audubon Data Project was initiated as a Clark University Capstone project. The project’s client, Mass Audubon’s Shaping the Future of Your Community program, had identified a need to improve their data management methods and make better use of their data. The Capstone team, composed of Clark University graduate students, met with the client regularly to review the current state of the data and potential improvements to be made. The process began with a data review. During the review we worked with the client to explicitly define the purposes and requirements of the data, the current process for updating and …

Towards A Physio-Cognitive Model Of Slow-Breathing, Chris Dancy

Faculty Conference Papers and Presentations

How may controlled breathing be beneficial, or detrimental to behavior? Computational process models are useful to specify the potential mechanisms that lead to behavioral adaptation during different breathing exercises. We present a physio-cognitive model of slow breathing implemented within a hybrid cognitive architecture, ACT-R/Φ. Comparisons to data from an experiment indicate that the physiological mechanisms are operating in a manner that is consistent with actual human function. The presented computational model provides predictions of ways that controlled breathing interacts with mechanisms of arousal to mediate cognitive behavior. The increasing use of breathing techniques to counteract effects of stressors makes it …

Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad

Wayne State University Dissertations

Massive amount of electronic medical records (EMRs) accumulating from patients and populations motivates clinicians and data scientists to collaborate for the advanced analytics to create knowledge that is essential to address the extensive personalized insights needed for patients, clinicians, providers, scientists, and health policy makers. Learning from large and complicated data is using extensively in marketing and commercial enterprises to generate personalized recommendations. Recently the medical research community focuses to take the benefits of big data analytic approaches and moves to personalized (precision) medicine. So, it is a significant period in healthcare and medicine for transferring to a new paradigm. …

Expression Of The Microrna-143/145 Cluster Is Decreased In Hepatitis B Virus-Associated Hepatocellular Carcinoma And May Serve As A Biomarker For Tumorigenesis In Patients With Chronic Hepatitis B, Qi Zhao, Xiangfei Sun, Chao Liu, Tao Li, Juan Cui, Chengyong Qin

School of Computing: Faculty Publications

The aims of the present study were to identify the expression profile of microRNA (miR)‑143/145 in hepatitis B virus (HBV)‑associated hepatocellular carcinoma (HCC), explore its association with prognosis and investigate whether the serum miR‑143/145 expression levels may serve as a diagnostic indicator of HBV‑associated HCC. The microRNA (miRNA) chromatin immunoprecipitation dataset was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus databases, and analyzed using the Wilcoxon signed‑rank test. It was observed that the expression of miR‑143 and miR‑145 was decreased 1.5‑fold in HBV‑associated HCC samples compared with non‑tumor tissue in the TCGA and the GSE22058 datasets …

Strategies For Healthcare Payer Information Technology Integration After Mergers And Acquisitions, Kishore Maranganti

Walden Dissertations and Doctoral Studies

Despite the high rate of failure in merger and acquisition (M&A) transactions, many organizations continue to rely on M&As as their primary growth strategy and to address market competition. The purpose of this qualitative single case study was to explore strategies managers from a large healthcare payer in the midwestern United States used to achieve operational and strategic synergies during the postacquisition information technology (IT) integration phase. Haspeslagh and Jemison's acquisition integration approaches model was the conceptual framework for the study. Methodological triangulation was established by analyzing the data from the semistructured interviews of 6 senior executives and 6 IT …

Research Agenda In Developing Core Reference Ontology For Human Intelligence/Machine-Intelligence Electronic Medical Records System, Ziniya Zahedi, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

Beginning around 1990, efforts were initiated in the medical profession by the U.S. government to transition from paper based medical records to electronic medical records (EMR). By the late 1990s, EMR implementation had already encountered multiple barriers and failures. Then President Bush set forth the goal of implementing electronic health records (EHRs), nationwide within ten years. Again, progress toward EMR implementation was not realized. President Obama put new emphasis on promoting EMR and health care technology. The renewed emphasis did not overcome many of the original problems and induced new failures. Retrospective analyses suggest that failures were induced because programmers …

Securing The Internet Of Healthcare, Michael Mattioli, Scott J. Shackelford, Steve Myers, Austin Brady, Yvette Wang, Stephanie Wong

Articles by Maurer Faculty

Cybersecurity, including the security of information technology (IT), is a critical requirement in ensuring society trusts, and therefore can benefit from, modern technology. Problematically, though, rarely a day goes by without a news story related to how critical data has been exposed, exfiltrated, or otherwise inappropriately used or accessed as a result of supply chain vulnerabilities. From the Russian government's campaign to influence the 2016 U.S. presidential election to the September 2017 Equifax breach of more than 140-million Americans' credit reports, mitigating cyber risk has become a topic of conversation in boardrooms and the White House, on Wall Street and …

The Impact Of Machine Learning Algorithms On Benchmarking Process In Healthcare Service Delivery, Egbe-Etu Emmanuel Etu

Wayne State University Theses

Currently, organizations have adopted and implemented a variety of innovative quality management philosophies, approaches, and techniques to stay competitive in an ever-changing global economy. Benchmarking is one of such techniques deployed by organizations to stay competitive. The motivation for this research stems from a real-world problem being faced by hospitals in the healthcare industry who have amassed a ton of data and want to embark on benchmarking project to assess the performance of the emergency departments due to challenges faced with poor management of operations which has led to high patient boarding rates, high patient wait-times, poor quality service, low …

Using The Qbest Equation To Evaluate Ellagic Acid Safety Data: Generating A Qnoael With Confidence Levels From Disparate Literature, Cynthia Rose Dickerson

Theses and Dissertations--Pharmacy

QBEST, a novel statistical method, can be applied to the problem of estimating the No Observed Adverse Effect Level (NOAEL or QNOAEL) of a New Molecular Entity (NME) in order to anticipate a safe starting dose for beginning clinical trials. The NOAEL from QBEST (called the QNOAEL) can be calculated using multiple disparate studies in the literature and/or from the lab. The QNOAEL is similar in some ways to the Benchmark Dose Method (BMD) used widely in toxicological research, but is superior to the BMD in some ways. The QNOAEL simulation generates an intuitive curve that is comparable to the …

Exploring Management Practices Of The Health Care System For Contractors, Gary L. Williams

Walden Dissertations and Doctoral Studies

Researchers have found that military members serving in war experienced changes in physical and mental health. Military members' healthcare is managed by the Department of Defense. The problem was that management practices of the system for providing long-term healthcare for employees of a contracting company working in foreign combat zones is either minimal or nonexistent. The purpose of this case study was to explore ways that contractor managers and government managers can work together to provide healthcare for those contract employees who will be deployed with the U.S. military. The primary research question was to determine what managers of contractors …

A Bi-Level Heuristic Solution For The Nurse Scheduling Problem Based On Shift-Swapping, Ahmed Youssef, Samah Senbel

School of Computer Science & Engineering Faculty Publications

This paper presents a new heuristic solution to the well-known Nurse Scheduling Problem (NSP). The NSP has a lot of constraints to satisfy. Some are mandatory and specified by the hospital administration, these are known as hard constraints. Some constraints are put by the nurses themselves to produce a comfortable schedule for themselves, and these are known as soft constraints. Our solution is based on the practice of shift swapping done by nurses after they receive an unsatisfactory schedule. The constraints are arranged in order of importance. Our technique works on two levels, first we generate a schedule that satisfies …

Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones

Theses and Dissertations--Computer Science

In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …

Mapping Opioid Mortality Rates Across Treatment Capacity To Identify Need And Access, Garrett K. Wong, Justin R. Chang, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow

Graduate Research Posters

Background: The opioid and heroin overdose epidemic is a public health emergency in the state of Virginia, resulting in the death of more than 1,100 people in 2016. In order to overcome this epidemic, we need to match the places with the greatest need for services related to substance use disorders with the appropriate healthcare workforce.

Aims: As the data about the overdose outbreak and related socioeconomic factors grow in size and complexity, data scientists have attempted to utilize big data techniques to identify communities and risk factors contributing to addiction.

Methods: Using data obtained from the …