Computer Sciences Commons^™

Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee

Research Collection School Of Computing and Information Systems

Addressing issue of crowding in an Emergency Department (ED) typically takes the form of process engineering or single-faceted queue management strategies such as demand restriction, queue prioritization or staffing the ED. This work provides an integrated framework to manage queue dynamically from both demand and supply perspectives. More precisely, we introduce intelligent dynamic patient prioritization strategies to manage the demand concurrently with dynamic resource adjustment policies to manage supply. Our framework allows decision-makers to select both the demand-side and supply-side strategies to suit the needs of their ED. We verify through a simulation that such a framework improves the patients' …

Flexiterm: A Flexible Term Recognition Method, Irena Spasić, Mark Greenwood, Alun Preece, Nick Francis, Glyn Elwyn

Dartmouth Scholarship

Background: The increasing amount of textual information in biomedicine requires effective term recognition methods to identify textual representations of domain-specific concepts as the first step toward automating its semantic interpretation. The dictionary look-up approaches may not always be suitable for dynamic domains such as biomedicine or the newly emerging types of media such as patient blogs, the main obstacles being the use of non-standardised terminology and high degree of term variation.

Use Of Immersive Visualization For The Control Of Dental Anxiety During Dental Hygiene Treatment, Carmelo Padrino-Barrios

Dental Hygiene Theses & Dissertations

Purpose: The purpose of this study was to determine the effectiveness of immersive visualization (IV) therapy, a technique that provides visual and stereoscopic display through the use of eyewear, in anxious patients during an oral prophylaxis. Methods: A convenience sample of thirty adults was enrolled. A split mouth design was utilized. Subjects were randomly divided into two groups: group A (use of IV for the right side of the mouth), and group B (use of IV for the left side of the mouth). Subjects received a full mouth oral prophylaxis (removal of supra and subgingival calculus and selective polishing), always …

Articulatory Distinctiveness Of Vowels And Consonants: A Data-Driven Approach, Jun Wang, Jordan R. Green, Ashok Samal, Yana Yunusova

School of Computing: Faculty Publications

Purpose: To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach.

Method: Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel pairs and consonant pairs were used to derive articulatory vowel and consonant spaces …

Writing For Publication In Biomedical Informatics Journals, Christoph Lehmann, Reinhold Haux, Jan Talmon, Dominik Aronsky, Nicolette De Keizer, Tze-Yun Leong, Charles Safran

Research Collection School Of Computing and Information Systems

No abstract provided.

Word Recognition From Continuous Articulatory Movement Time-Series Data Using Symbolic Representations, Jun Wang, Arvind Balasubramanian, Luis Mojica De La Vega, Jordan R. Green, Ashok Samal, Balakrishnan Prabhakaran

School of Computing: Conference and Workshop Papers

Although still in experimental stage, articulation-based silent speech interfaces may have significant potential for facilitating oral communication in persons with voice and speech problems. An articulation-based silent speech interface converts articulatory movement information to audible words. The complexity of speech production mechanism (e.g., co-articulation) makes the conversion a formidable problem. In this paper, we reported a novel, real-time algorithm for recognizing words from continuous articulatory movements. This approach differed from prior work in that (1) it focused on word-level, rather than phoneme-level; (2) online segmentation and recognition were conducted at the same time; and (3) a symbolic representation (SAX) was …

Renal Cryoablation: Investigation Of Periprocedural Visualization To Ols And Treatment Response Quantification, Katherine L. Dextraze

Dissertations and Theses (Open Access)

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in …

Algorithms And A Software Application For The Discovery Of Heparin-Binding Proteins For Chemical Analysis, Christopher Dempewolf

Computer Science and Computer Engineering Undergraduate Honors Theses

Heparin is a biological molecule that plays a vital role in anticoagulation. As such, it is used for the prevention of blood clotting in a variety of medical disorders. However, it is easily contaminated with foreign substances, and this can prove fatal for a person receiving heparin. In order to prevent this, proteins that easily bind to heparin need to be added to the solution. Then, the unwanted substances can easily be filtered out. Certain sequences or patterns of amino acids are known to have a high probability of binding to heparin. Thus, proteins that contain large numbers of these …

Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …

Diffusion Of Mobile Payment Systems Among Microentrepreneurs In Kenya And Tanzania, Dionne Nickerson

Annual Celebration of Student Scholarship and Creativity

The rapid rise of Kenya's mobile payment system, M-PESA , has grasped the attention of policy makers and private enterprise alike. In just six years M-PESA has transformed how money flows throughout Kenya, and similar systems are gaining traction elsewhere in Africa. This project examines the impact of mobile payment system adoption on the economic advancement of Kenyan and Tanzanian microentrepreneurs. This work will further the understanding of mobile payment systems’ contribution to the economic growth of microenterprises, which may have implications for poverty reduction in these two nations.

Volume 05, Ian Karamarkovich, Jessica Cox, Kyle Fowlkes, Allison Pawlowski, Kaitlin Major, Carrie Dunham, Kelsey Scheitlin, Kathryn Grayson, Ashley Johnson, Jennifer Nehrt, Kelsey Stolzenbach, Kristin Mcquarrie, Sara Nelson, Melisa Michelle, Jessica Sudlow, Perry Bason, Danielle Dmuchawski, Mariah Asbell, Matthew Sakach, Timothy Smith Jr., Annaliese Troxell, T. Dane Summerell, Sarah Ganrude, Malina Rutherford, Hannah Hopper, John Berry Jr., James Early, Colleen Festa, Chelsea D. Taylor, Michelle Maddox, Kaitlyn Smith, Sarah Schu, Cabell Edmunds, Katherine Grayson, Kayla Tornai

Incite: The Journal of Undergraduate Scholarship

Introduction from Dean Dr. Charles Ross

The Tallis House as an Extension of Emily Tallis in McEwan's Atonement by Ian Karamarkovich

Graphic Design by Jessica Cox

Graphic Design by Kyle Fowlkes

Graphic Design by Allison Pawlowski

Incorporating Original Research in The Classroom: A Case Study Analyzing the Influence of the Chesapeake Bay on Local Temperatures by Kaitlin Major, Carrie Dunham and Dr. Kelsey Scheitlin

Graphic Design by Kathryn Grayson

Graphic Design by Ashley Johnson

Facing the Music: Environmental Impact Assessment of Building A Concert Hall on North Campus by Jennifer Nehrt, Kelsey Stolzenbach And Dr. Kelsey Scheitlin

Art by Kristin …

Online Survey System For Image-Based Clinical Guideline Studies Using The Delphi Method, Todd Martin Harper

Theses and Dissertations

The increasing use of health information technology (HIT) is due to a rising interest in improving the quality of health care. HIT has the potential to reduce cost and transform services. Proper clinical support systems will contribute to the meaningful use of HIT systems by providing a wide array of data to clinicians for the diagnosis and treatments. Clinical guidelines, created by a consensus of experts, can be put in place to assist physicians in making clinical decisions. Delphi methods are commonly used to create consensus from surveys completed by a team of experts. Image-based studies could create guidelines that …

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …

Examining Advances In Technology And Hospitality Information Strategy, Robert J. Kauffman, P. Oconnor

Research Collection School Of Computing and Information Systems

Hospitality managers have turned to IT to streamline reservations, capture new customer data, and build market share. Internet-based reservations, advertising and communication, social media, and mobile phones offer technology-led opportunities for value cocreation with customers. We aim to stimulate sharing of new ideas, current applications and emerging managerial know-how for the hospitality industry, while bringing new submissions to CQ.

Special Issue On Medical Simulation, Michel Audette, Hanif M. Ladak

Computational Modeling & Simulation Engineering Faculty Publications

We would like to welcome you to this Special Issue on Medical Simulation, the first of its kind not only for SIMULATION: Transactions of The Society for Modeling and Simulation International, but for any technical journal. Our respective backgrounds are an indication of the technical and clinical breadth of medical simulation, as we approach the subject as primarily medical image analysis and biomechanics experts respectively, each with a variety of clinical interests spanning virtual reality (VR)–based neuro-, orthopedic and ear-nose-and-throat surgery. Moreover, we believe that the breadth of the papers that comprise this issue reflects an even broader perspective. After …

Impact Of Varied Low Resolution Phantoms On Intensity Modulated Proton Therapy Dose Distributions, Aarohi Shyam Padhye

Theses Digitization Project

The primary purpose of this thesis is to discuss the usefulness of image segmentation techniques in creating accurate proton dose distribution plans. The calculation of the proton dose distribution has to take into account the material (tissue, bone, brain) in the treatment area of the patients body.

Stereotactic Localization And Targeting Accuracy For Experimental Proton Radiosurgery, Yin Chen

Theses Digitization Project

The purpose of this study was to improve an existing experimental proton radiosurgery system at Loma Linda University Medical Center to reach sub-millimeter accuracy before proton radiosurgery with narrow beams can be used in a clinical trial. Protons, different from photons (i.e., x-rays or gamma rays), are charged with particles that slow down in matter and release a burst of energy near the end of their range (maximum depth of penetration), which is called the Bragg peak, named after the physicist William Henry Bragg who discovered it in 1903. Photon beams deliver most doses over a large area near the …

Fiducial-Free Alignment Verification Techniques For Intracranial Radiosurgery, Kenneth Matthew Williams

Theses Digitization Project

This thesis serves as the basis for a method using image registration to automate patient alignment in an effort to eliminate the dependency on the fiducial markers as well as improve the accuracy efficiency of the alignment process. Proton beams are an external beam modality of radiation therapy that can be used effectively for radiosurgical applications due to the dosimetry advantage of the Bragg peak. The Bragg peak is a phenomenon exploited by proton beam therapy to concentrate the effect of the beams on the tumor while minimizing damage to critical structures and other health tissues within the patient.

Dependence On Cyberscribes - Issues In E-Security, Thomas R. Mclean, Alexander B. Mclean

Journal of Business & Technology Law

No abstract provided.

A New Phantom And Gradient Isocenter Estimation For Magnetic Resonance Imaging Distortion Correction, Zongqi Cai

Theses Digitization Project

The purpose of this study was to develop and implement a numerical software based method that can accurately correct the distortion of MR images generated by 3T MRI scanner. To accomplish this, a new phantom has been designed from scratch to capture the distortions inside 3T MRI scanner. An algorithm has been developed, based on the unique geometric feature of the new phantom, to estimate the location of gradient isocenter of the magnetic field inside 3T MRI scanner for the first time.

Alternative Hull Detection Techniques For Preprocessing In Proton Computed Tomography Reconstruction, Blake Edward Schultze

Theses Digitization Project

The purpose of this study was to develop computationally efficient hull detection techniques appropriate for image reconstruction using sparse matrices. The hull detection techniques investigated were space carving (SC), modified space carving (MSC), and space modeling (SM) and these were compared to the cone-beam version of filtered back projection (FBP) algorithm in terms of their computation time and the quality of the object hull they produced.

‘What’S In The Niddk Cdr?’—Public Query Tools For The Niddk Central Data Repository, Huaqin Pan, Mary-Anne Ardini, Vesselina Bakalov, Michael Delatte, Paul Eggers, Laxminarayana Ganapathi, Craig R. Hollingsworth, Joshua Levy, Sheping Li, Joseph Pratt, Norma Pugh, Ying Qin, Rebekah Rasooly, Helen Ray, Jean E. Richardson, Amanda Flynn Riley, Susan M. Rogers, Sylvia Tan, Charles F. Turner, Stacie White, Philip C. Cooley

Publications and Research

The National Institute of Diabetes and Digestive Disease (NIDDK) Central Data Repository (CDR) is a web-enabled resource available to researchers and the general public. The CDR warehouses clinical data and study documentation from NIDDK funded research, including such landmark studies as The Diabetes Control and Complications Trial (DCCT, 1983–93) and the Epidemiology of Diabetes Interventions and Complications (EDIC, 1994–present) follow-up study which has been ongoing for more than 20 years. The CDR also houses data from over 7 million biospecimens representing 2 million subjects. To help users explore the vast amount of data stored in the NIDDK CDR, we developed …

Nfl: The World Of Technology?: How Technology Made The Nfl The Cash Cows Of The Sports World, Jaron A. Moody

Senior Seminars

Sports coverage is highly focused on the image of the sport and how the fans experience the sport. Technology plays a huge part of that. The technology that's used to maintain the display of the game as well as the technology that holds the statistics that keeps fans fully aware about what's going on in the game. The IT department has to work with programmers to create these programs and they have to keep them up to date. Without this, the experience of watching sports on television would decrease rapidly which would send the value of the NFL to a …

Technology Use In The National Basketball Association: How Technology And Communication Has Changed, Katie Hottinger

Senior Seminars

No abstract provided.

A Machine Learning Approach To Diagnosis Of Parkinson’S Disease, Sumaiya F. Hashmi

CMC Senior Theses

I will investigate applications of machine learning algorithms to medical data, adaptations of differences in data collection, and the use of ensemble techniques.

Focusing on the binary classification problem of Parkinson’s Disease (PD) diagnosis, I will apply machine learning algorithms to a primary dataset consisting of voice recordings from healthy and PD subjects. Specifically, I will use Artificial Neural Networks, Support Vector Machines, and an Ensemble Learning algorithm to reproduce results from [MS12] and [GM09].

Next, I will adapt a secondary regression dataset of PD recordings and combine it with the primary binary classification dataset, testing various techniques to consolidate …

Privacy And Security Issues In Iot Healthcare Applications For The Disabled Users A Survey, Wassnaa Al-Mawee

Masters Theses

Aging of the population resulted in new challenges for the society and healthcare systems. Ambient Assisted Living (AAL) that depends on Internet of Things (IoT) provides assistance to the disabled people and supports their vital daily life activities. Affordability of and accessibility to AAL and the usage of IoT starts revolutionizing healthcare services. This Thesis is a survey of the privacy and security issues in IoT healthcare applications for the disabled users. Introduction includes definitions of privacy and security terms, and discusses their relationship. Then, it presents an overview of the IoT, including its architecture and components. Next, the Thesis …

Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi

School of Computing: Conference and Workshop Papers

Data mining of protein databases poses special challenges because many protein databases are non- relational whereas most data mining and machine learning algorithms assume the input data to be a type of rela- tional database that is also representable as an ARFF file. We developed a method to restructure protein databases so that they become amenable for various data mining and machine learning tools. Our restructuring method en- abled us to apply both decision tree and support vector machine classifiers to a pancreatic protein database. The SVM classifier that used both GO term and PFAM families to characterize proteins gave …

Design And Optimization Of Four-Dimensional Cone-Beam Computed To Mography In Image-Guided Radiation Therapy, Moiz Ahmad

Dissertations and Theses (Open Access)

The influence of respiratory motion on patient anatomy poses a challenge to accurate radiation therapy, especially in lung cancer treatment. Modern radiation therapy planning uses models of tumor respiratory motion to account for target motion in targeting. The tumor motion model can be verified on a per-treatment session basis with four-dimensional cone-beam computed tomography (4D-CBCT), which acquires an image set of the dynamic target throughout the respiratory cycle during the therapy session. 4D-CBCT is undersampled if the scan time is too short. However, short scan time is desirable in clinical practice to reduce patient setup time. This dissertation presents the …

An Automated Pathological Class Level Annotation System For Volumetric Brain Images, Thien Anh Dinh, Tomi Silander, C. C. Tchoyoson Lim, Tze-Yun Leong

Research Collection School Of Computing and Information Systems

We introduce an automated, pathological class level annotation system for medical volumetric brain images. While much of the earlier work has mainly focused on annotating regions of interest in medical images, our system does not require annotated region level training data nor assumes perfect segmentation results for the regions of interest; the time and effort needed for acquiring training data are hence significantly reduced. This capability of handling high-dimensional noisy data, however, poses additional technical challenges, since statistical estimation of models for such data is prone to over-fitting. We propose a framework that combines a regularized logistic regression method and …

Privacy In Mobile Technology For Personal Healthcare, Sasikanth Avancha, Amit Baxi, David Kotz

Dartmouth Scholarship

Information technology can improve the quality, efficiency, and cost of healthcare. In this survey, we examine the privacy requirements of \emphmobile\/ computing technologies that have the potential to transform healthcare. Such \emphmHealth\/ technology enables physicians to remotely monitor patients' health, and enables individuals to manage their own health more easily. Despite these advantages, privacy is essential for any personal monitoring technology. Through an extensive survey of the literature, we develop a conceptual privacy framework for mHealth, itemize the privacy properties needed in mHealth systems, and discuss the technologies that could support privacy-sensitive mHealth systems. We end with a list of …