Computer Sciences Commons^™

Real-Time Ultrasound Simulation For Medical Training And Standardized Patient Assessment, Bo Sun

Computational Modeling & Simulation Engineering Theses & Dissertations

With the increasing role played by ultrasound in clinical diagnostics, ultrasound training in medical education has become more and more important. The clinical routine for ultrasound training is on real patients; therefore monitored and guided examinations involving medical students are quite time-constrained. Furthermore, standardized patients (SPs), who are increasingly used in medical school for teaching and assessing medical students, need to be augmented. These SPs are typically healthy individuals who can not accurately portray the variety of abnormalities that are needed for training especially when medical examinations involve instrument interactions. To augment SPs in a realistically effective way and also …

Volume 01, Jessica Fields, Stephanie Neeley, Derek W. Hambright, Mary E. Lehman, Andrew R. Grzankowski, Zachary Johnson, Boone M. Prentice, Ashley M. Swandby, Victoria Morgan, Katie Williamson, Kristine G. Bender, Katelyn N. Romaine, D. Nicole Swann, Jessica Fox, Mike Mcateer, Alex Grabiec, Laura Nodtvedt, Nick Costa, Rachel Wolfe, Zack Dalton

Incite: The Journal of Undergraduate Scholarship

Introduction from Dean Dr. Charles Ross

Three Decades of Digging: Undergraduate Archeology at Longwood by Jessica Fields and Stephanie Neeley

Interactions of Allelopathy and Heat Stress in Plants by Derek W. Hambright and Mary E. Lehman

Inertial Electrostatic Confinement D-D Fusion Device: Construction and Simulation by Andrew R. Grzankowski

Shackled Nim by Zachary Johnson

Development of GC-MS and Chemometric Methods for the Analysis of Accelerants in Arson Cases by Boone M. Prentice

A Comparison of Image Analysis Methods in cDNA Microarrays by Ashley M. Swandby

Perceived Sexual Activity of Short and Long-Term Relationships by Victoria Morgan and Katie Williamson

Elderly …

A Delphi Study Assessing Long-Term Access To Electronic Medical Records (Emr), Byron D. Nicholson

Theses and Dissertations

This research effort addressed the issue of long-term access to electronic medical records as technological generations become obsolete, thereby preventing the access to patient health information. Using the Delphi methodology, experts with experience in electronic medical records and applicable systems provided insight based on their years of hands-on experience managing and/or using records and these systems. The end result of this research was a collection of ideas that medical institutions and medical informaticians must consider to ensure that patients and hospitals do not lose long-term access to electronic medical records as electronic medical records and technology continually evolves. Results of …

Prostate Segmentation On Pelvic Ct Images Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell

Computer Science Faculty Publications and Presentations

A genetic algorithm (GA) for automating the segmentation of the prostate on pelvic computed tomography (CT) images is presented here. The images consist of slices from three-dimensional CT scans. Segmentation is typically performed manually on these images for treatment planning by an expert physician, who uses the “learned” knowledge of organ shapes, textures and locations to draw a contour around the prostate. Using a GA brings the flexibility to incorporate new “learned” information into the segmentation process without modifying the fitness function that is used to train the GA. Currently the GA uses prior knowledge in the form of texture …

Droid: The Drosophila Interactions Database, A Comprehensive Resource For Annotated Gene And Protein Interactions, Jingkai Yu, Svetlana Pacifico, Guozhen Liu, Russell L. Finley Jr

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, Drosophila melanogaster. …

Object Detection And Classification With Applications To Skin Cancer Screening, Jonathan Blackledge, Dmitryi Dubovitskiy

Articles

This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

The principal issues associated with object recognition are presented which includes two novel fast segmentation algorithms for which C++ code is provided. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and …

Century: Automated Aspects Of Patient Care, Marion Blount, John Davis, Maria Ebling, Ji Hyun Kim, Kyun Hyun Kim, Kang Yoon Lee, Archan Misra, Se Hun Park, Daby Sow, Young Ju Tak, Min Wang, Karen Witting

Research Collection School Of Computing and Information Systems

Remote health monitoring affords the possibility of improving the quality of health care by enabling relatively inexpensive out-patient care. However, remote health monitoring raises new a problem: the potential for data explosion in health care systems. To address this problem, the remote health monitoring systems must be integrated with analysis tools that provide automated trend analysis and event detection in real time. In this paper, we propose an overview of Century, an extensible framework for analysis of large numbers of remote sensor-based medical data streams.

Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng

Research Collection School Of Computing and Information Systems

Coronary artery disease (CAD) is a main cause of death in the world. Finding cost-effective methods to predict CAD is a major challenge in public health. In this paper, we investigate the combined effects of genetic polymorphisms and non-genetic factors on predicting the risk of CAD by applying well known classification methods, such as Bayesian networks, naïve Bayes, support vector machine, k-nearest neighbor, neural networks and decision trees. Our experiments show that all these classifiers are comparable in terms of accuracy, while Bayesian networks have the additional advantage of being able to provide insights into the relationships among the variables. …

Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Undetected errors in the expression measurements from highthroughput DNA microarrays and protein spectroscopy could seriously affect the diagnostic reliability in disease detection. In addition to a high resilience against such errors, diagnostic models need to be more comprehensible so that a deeper understanding of the causal interactions among biological entities like genes and proteins may be possible. In this paper, we introduce a robust knowledge discovery approach that addresses these challenges. First, the causal interactions among the genes and proteins in the noisy expression data are discovered automatically through Bayesian network learning. Then, the diagnosis of a disease based on …

A Time-And-Value Centric Provenance Model And Architecture For Medical Event Streams, Marion Bllount, John Davis, Archan Misra, Daby Sow, Min Wang

Research Collection School Of Computing and Information Systems

Provenance becomes a critical requirement for healthcare IT infrastructures, especially when pervasive biomedical sensors act as a source of raw medical streams for large-scale, automated clinical decision support systems. Medical and legal requirements will make it obligatory for such systems to answer queries regarding the underlying data samples from which output alerts are derived, the IDs of the processing components used and the privileges of the individuals and software components accessing the medical data. Unfortunately, existing models of either annotation or process based provenance are designed for transaction-oriented systems and do not satisfy the unique requirements for systems processing high-volume, …

A Day In The Life Of Pubmed: Analysis Of A Typical Day's Query Log, Jorge R Herskovic, Len Y Tanaka, William Hersh, Elmer V Bernstam

Faculty, Staff and Student Publications

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of …

Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara

Electrical & Computer Engineering Faculty Publications

We evaluate and improve an existing curvature-based region growing algorithm for colonic polyp detection for our CT colonography (CTC) computer-aided detection (CAD) system by using Pareto fronts. The performance of a polyp detection algorithm involves two conflicting objectives, minimizing both false negative (FN) and false positive (FP) detection rates. This problem does not produce a single optimal solution but a set of solutions known as a Pareto front. Any solution in a Pareto front can only outperform other solutions in one of the two competing objectives. Using evolutionary algorithms to find the Pareto fronts for multi-objective optimization problems has been …

Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett

Electrical & Computer Engineering Faculty Publications

Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).

Methods: Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis …

Validating Pareto Optimal Operation Parameters Of Polyp Detection Algorithms For Ct Colonography, Jiang Li, Adam Huang, Nicholas Petrick, Jianhua Yao, Ronald M. Summers, Maryellen L. Giger (Ed.), Nico Karssemeijer (Ed.)

Electrical & Computer Engineering Faculty Publications

We evaluated a Pareto front-based multi-objective evolutionary algorithm for optimizing our CT colonography (CTC) computer-aided detection (CAD) system. The system identifies colonic polyps based on curvature and volumetric based features, where a set of thresholds for these features was optimized by the evolutionary algorithm. We utilized a two-fold cross-validation (CV) method to test if the optimized thresholds can be generalized to new data sets. We performed the CV method on 133 patients; each patient had a prone and a supine scan. There were 103 colonoscopically confirmed polyps resulting in 188 positive detections in CTC reading from either the prone or …

Information Governance: A Model For Security In Medical Practice, Patricia Williams

Research outputs pre 2011

Information governance is becoming an important aspect of organisational accountability. In consideration that information is an integral asset of most organisations, the protection of this asset will increasingly rely on organisational capabilities in security. In the medical arena this information is primarily sensitive patient-based information'. Previous research has shown that application of security measures is a low priority for primary care medical practice and that awareness of the risks are seriously underestimated. Consequently, information security governance will be a key issue for medical practice in the future. Information security governance is a relatively new term ,and there is little existing …

Development And Implementation Of Optimized Energy-Delay Sub-Network Routing Protocol For Wireless Sensor Networks, James W. Fonda, Maciej Zawodniok, S. Jagannathan, Steve E. Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

The development and implementation of the optimized energy-delay sub-network routing (OEDSR) protocol for wireless sensor networks (WSN) is presented. This on demand routing protocol minimizes a novel link cost factor which is defined using available energy, end-to-end (E2E) delay and distance from a node to the base station (BS), along with clustering, to effectively route information to the BS. Initially, the nodes are either in idle or sleep mode, but once an event is detected, the nodes near the event become active and start forming sub-networks. Formation of the inactive network into a sub-network saves energy because only a portion …

Set-Based Cascading Approaches For Magnetic Resonance (Mr) Image Segmentation (Scamis), Jiang Liu, Tze-Yun Leong, Kin Ban Chee, Boon Pin Tan, Borys Shuter, Shih Chang Wang

Research Collection School Of Computing and Information Systems

This paper introduces Set-based Cascading Approach for Medical Image Segmentation (SCAMIS), a new methodology for segmentation of medical imaging by integrating a number of algorithms. Existing approaches typically adopt the pipeline methodology. Although these methods provide promising results, the results generated are still susceptible to over-segmentation and leaking. In our methodology, we describe how set operations can be utilized to better overcome these problems. To evaluate the effectiveness of this approach, Magnetic Resonance Images taken from a teaching hospital research programme have been utilised, to reflect the real world quality needed for testing in patient datasets. A comparison between the …

An Event-Driven Approach To Computerizing Clinical Guidelines Using Xml, Bing Wu, Essam Mansour, Kudakwashe Dube, Jianxin Li

Conference Papers

Clinical events form the basis of patient care practice. Their computerization is an important aid to the work of clinicians. Clinical guidelines or protocols direct clinicians and patients on when and how to handle clinical problems. Thus, clinical guidelines are an encapsulation of clinical events. Hence, an event-driven approach to computerizing the management of clinical guidelines is worthy of investigation. In our framework, called SpEM, the main clinical guideline management dimensions are specification, execution, and manipulation. This paper presents an event-driven approach, within the context of the SpEM framework, to manage clinical guidelines. The event-driven approach is based on the …

Gaussian Mixture Models And Neural Networks For Automatic Speaker Identification, Usha Gayatri Chalkapally

Electrical & Computer Engineering Theses & Dissertations

Automatic Speaker Recognition is the process of automatically recognizing who is speaking on the basis of individual information contained in speech signals. This technique of Automatic Speaker Recognition makes it possible to use the speaker's voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers.

In this thesis, the techniques of Gaussian Mixture Models and Neural Networks for Automatic Speaker Identification are presented. Algorithms for Speaker Identification using Gaussian Mixture Models were developed, …

Mobile Healthcare Informatics, Keng Siau, Zixing Shen

Research Collection School Of Computing and Information Systems

Advances in wireless technology give pace to the rapid development of mobile applications. The coming mobile revolution will bring dramatic and fundamental changes to our daily life. It will influence the way we live, the way we do things, and the way we take care of our health. For the healthcare industry, mobile applications provide a new frontier in offering better care and services to patients, and a more flexible and mobile way of communicating with suppliers and patients. Mobile applications will provide important real time data for patients, physicians, insurers, and suppliers. In addition, it will revolutionalize the way …

A Short Tutorial On Reconstructability Analysis, Martin Zwick

Complex Systems Faculty Publications and Presentations

This talk will present the basic ideas of Reconstructability Analysis. RA is a general modeling methodology developed in the systems community since the early 60s (pioneered by Ross Ashby) for exploratory (data mining, machine learning) and confirmatory modeling. RA is based in graph theory, set theory, information theory, and statistics. It is applicable to qualitative (nominal) and, via binning, to quantitative (continuous) data, with both statistical & non-statistical applications. It overlaps and augments more widely known methods, e.g., log-linear modeling and Bayesian networks.

Keywords: Reconstructability Analysis, Log-Linear Modeling, categorical data, multivariate statistics, exploratory modeling, confirmatory modeling

Batch Mode Active Learning And Its Applications To Medical Image Classification, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu

Research Collection School Of Computing and Information Systems

The goal of active learning is to select the most informative examples for manual labeling. Most of the previous studies in active learning have focused on selecting a single unlabeled example in each iteration. This could be inefficient since the classification model has to be retrained for every labeled example. In this paper, we present a framework for "batch mode active learning" that applies the Fisher information matrix to select a number of informative examples simultaneously. The key computational challenge is how to efficiently identify the subset of unlabeled examples that can result in the largest reduction in the Fisher …

A Framework For The Representation Of Cohesion In Small Combat Units, William Eugene Warner

Computational Modeling & Simulation Engineering Theses & Dissertations

Current combat simulations deal well with large unit formations, weapon systems, and physical effects such as attrition. Human factors such as morale, cohesion, and effects of stress are modeled much less adequately. Of the human factors affecting the psychology of a combat unit, military psychologists have identified cohesion as one of the most important. The concept of cohesion, referring to both the interpersonal relationships between soldiers in a military unit and to the morale solidarity of a military force, has been central to military analysis for many years.

A model framework has been developed that can operationalize the concept of …

Fortifying Password Authentication In Integrated Healthcare Delivery Systems, Yanjiang Yang, Robert H. Deng, Feng Bao

Research Collection School Of Computing and Information Systems

Integrated Delivery Systems (IDSs) now become a primary means of care provision in healthcare domain. However, existing password systems (under either the single-server model or the multi-server model) do not provide adequate security when applied to IDSs. We are thus motivated to present a practical password authentication system built upon a novel two-server model. We generalize the two-server model to an architecture of a single control server supporting multiple service servers, tailored to the organizational structure of IDSs. The underlying user authentication and key exchange protocols we propose are password-only, neat, efficient, and robust against off-line dictionary attacks mounted by …

Using A Digital Library Of Images For Communication: Comparison Of A Card-Based System To Pda Software, Trudi Miller '08, Gondy Leroy, John Huang '05, Serena Chuang '05

CGU Faculty Publications and Research

Autism spectrum disorder has become one of the most prevalent developmental disorders and one of the main impairments is difficulty with communication. One method of augmentative and alternative communication is the use of the Picture Exchange Communication System (PECS) to create messages using a series of images printed on cards and organized in binders. We are developing a digital alternative based on an image library that is displayed on a personal digital assistant (PDA). We conducted an initial user acceptance study that compared the effectiveness and usability of both systems. The study showed that the PDA system was able to …

Health Information Text Characteristics, Gondy Leroy, Evren Eryilmaz '11, Benjamin T. Laroya

CGU Faculty Publications and Research

Millions of people search online for medical text, but these texts are often too complicated to understand. Readability evaluations are mostly based on surface metrics such as character or words counts and sentence syntax, but content is ignored. We compared four types of documents, easy and difficult WebMD documents, patient blogs, and patient educational material, for surface and content-based metrics. The documents differed significantly in reading grade levels and vocabulary used. WebMD pages with high readability also used terminology that was more consumer-friendly. Moreover, difficult documents are harder to understand due to their grammar and word choice and because they …

Multinational Web Uses And Gratifications: Measuring The Social Impact Of Online Community Participation Across National Boundaries, Patricia Grace-Farfaglia, Ad Dekkers, Binod Sundararajan, Lois Peters, Sung-Hee Park

Nutrition Sciences Faculty Publications

This paper describes the rationale and findings from a multinational study of online uses and gratifications conducted in theUnited States,Korea, and theNetherlandsin spring 2003. Survey questions developed in three languages by native speaking researchers was presented to approximately 400 respondents in each country via the Web. Web uses and gratifications were analyzed cross-nationally in a comparative fashion focusing on involvement in different types of on-line communities. Findings indicate that demographic characteristics, cultural values, and Internet connection type emerged as critical factors that explain why the same technology is adopted differently.

Dynamic Generation Of A Table Of Contents With Consumer-Friendly Labels, Trudi Miller '08, Gondy Leroy, Elizabeth Wood

CGU Faculty Publications and Research

Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than with …

A Database And Tool, Im Browser, For Exploring And Integrating Emerging Gene And Protein Interaction Data For Drosophila, Svetlana Pacifico, Guozhen Liu, Stephen Guest, Jodi R. Parrish, Farshad Fotouhi, Russell L. Finley Jr

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Biological processes are mediated by networks of interacting genes and proteins. Efforts to map and understand these networks are resulting in the proliferation of interaction data derived from both experimental and computational techniques for a number of organisms. The volume of this data combined with the variety of specific forms it can take has created a need for comprehensive databases that include all of the available data sets, and for exploration tools to facilitate data integration and analysis. One powerful paradigm for the navigation and analysis of interaction data is an interaction graph or map that represents proteins …

Interdependency Of Pharmacokinetic Parameters: A Chicken-And-Egg Problem? Not!, Reza Mehvar

Pharmacy Faculty Articles and Research

Pharmacokinetic (PK) software packages are widely used by scientists in different disciplines to estimate PK parameters. However, their use without a clear understanding of physiological parameters affecting the PK parameters and how different PK parameters are related to each other may result in erroneous interpretation of data. Often, mathematical relationships used for the estimation of PK parameters obscure the true physiological relationships among these parameters, prompting a discussion of which parameter came first and giving the appearance of the-chicken-and-the-egg dilemma. In this article, the author attempts to show how different PK parameters are related to physiological parameters and each other …