8 resultados para medical intrascopy systems

em Digital Commons at Florida International University


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In the medical field images obtained from high definition cameras and other medical imaging systems are an integral part of medical diagnosis. The analysis of these images are usually performed by the physicians who sometimes need to spend long hours reviewing the images before they are able to come up with a diagnosis and then decide on the course of action. In this dissertation we present a framework for a computer-aided analysis of medical imagery via the use of an expert system. While this problem has been discussed before, we will consider a system based on mobile devices. Since the release of the iPhone on April 2003, the popularity of mobile devices has increased rapidly and our lives have become more reliant on them. This popularity and the ease of development of mobile applications has now made it possible to perform on these devices many of the image analyses that previously required a personal computer. All of this has opened the door to a whole new set of possibilities and freed the physicians from their reliance on their desktop machines. The approach proposed in this dissertation aims to capitalize on these new found opportunities by providing a framework for analysis of medical images that physicians can utilize from their mobile devices thus remove their reliance on desktop computers. We also provide an expert system to aid in the analysis and advice on the selection of medical procedure. Finally, we also allow for other mobile applications to be developed by providing a generic mobile application development framework that allows for access of other applications into the mobile domain. In this dissertation we outline our work leading towards development of the proposed methodology and the remaining work needed to find a solution to the problem. In order to make this difficult problem tractable, we divide the problem into three parts: the development user interface modeling language and tooling, the creation of a game development modeling language and tooling, and the development of a generic mobile application framework. In order to make this problem more manageable, we will narrow down the initial scope to the hair transplant, and glaucoma domains.

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The deployment of wireless communications coupled with the popularity of portable devices has led to significant research in the area of mobile data caching. Prior research has focused on the development of solutions that allow applications to run in wireless environments using proxy based techniques. Most of these approaches are semantic based and do not provide adequate support for representing the context of a user (i.e., the interpreted human intention.). Although the context may be treated implicitly it is still crucial to data management. In order to address this challenge this dissertation focuses on two characteristics: how to predict (i) the future location of the user and (ii) locations of the fetched data where the queried data item has valid answers. Using this approach, more complete information about the dynamics of an application environment is maintained. ^ The contribution of this dissertation is a novel data caching mechanism for pervasive computing environments that can adapt dynamically to a mobile user's context. In this dissertation, we design and develop a conceptual model and context aware protocols for wireless data caching management. Our replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore a good candidate for eviction when cache space is needed. The context aware driven prefetching algorithm exploits the query context to effectively guide the prefetching process. The query context is defined using a mobile user's movement pattern and requested information context. Numerical results and simulations show that the proposed prefetching and replacement policies significantly outperform conventional ones. ^ Anticipated applications of these solutions include biomedical engineering, tele-health, medical information systems and business. ^

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This dissertation presents and evaluates a methodology for scheduling medical application workloads in virtualized computing environments. Such environments are being widely adopted by providers of "cloud computing" services. In the context of provisioning resources for medical applications, such environments allow users to deploy applications on distributed computing resources while keeping their data secure. Furthermore, higher level services that further abstract the infrastructure-related issues can be built on top of such infrastructures. For example, a medical imaging service can allow medical professionals to process their data in the cloud, easing them from the burden of having to deploy and manage these resources themselves. In this work, we focus on issues related to scheduling scientific workloads on virtualized environments. We build upon the knowledge base of traditional parallel job scheduling to address the specific case of medical applications while harnessing the benefits afforded by virtualization technology. To this end, we provide the following contributions: (1) An in-depth analysis of the execution characteristics of the target applications when run in virtualized environments. (2) A performance prediction methodology applicable to the target environment. (3) A scheduling algorithm that harnesses application knowledge and virtualization-related benefits to provide strong scheduling performance and quality of service guarantees. In the process of addressing these pertinent issues for our target user base (i.e. medical professionals and researchers), we provide insight that benefits a large community of scientific application users in industry and academia. Our execution time prediction and scheduling methodologies are implemented and evaluated on a real system running popular scientific applications. We find that we are able to predict the execution time of a number of these applications with an average error of 15%. Our scheduling methodology, which is tested with medical image processing workloads, is compared to that of two baseline scheduling solutions and we find that it outperforms them in terms of both the number of jobs processed and resource utilization by 20–30%, without violating any deadlines. We conclude that our solution is a viable approach to supporting the computational needs of medical users, even if the cloud computing paradigm is not widely adopted in its current form.

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The current U.S. health care system faces numerous environmental challenges. To compete and survive, health care organizations are developing strategies to lower costs and increase efficiency and quality. All of these strategies require rapid and precise decision making by top level managers. The purpose of this study is to determine the relationship between the environment, made up of unfavorable market conditions and limited resources, and the work roles of top level managers, specifically in the settings of academic medical centers. Managerial work roles are based on the ten work roles developed by Henry Mintzberg, in his book, The Nature of Managerial Work (1973). ^ This research utilized an integrated conceptual framework made up of systems theory in conjunction with role, attribution and contingency theories to illustrate that four most frequently performed Mintzberg's work roles are affected by the two environment dimensions. The study sample consisted of 108 chief executive officers in academic medical centers throughout the United States. The methods included qualitative methods in the form of key informants and case studies and quantitative in the form of a survey questionnaire. Research analysis involved descriptive statistics, reliability tests, correlation, principal component and multivariate analyses. ^ Results indicated that under the market condition of increased revenue based on capitation, the work roles increased. In addition, under the environment dimension of limited resources, the work roles increased when uncompensated care increased while Medicare and non-government funding decreased. ^ Based on these results, a typology of health care managers in academic medical centers was created. Managers could be typed as a strategy-formulator, relationship-builder or task delegator. Therefore, managers who ascertained their types would be able to use this knowledge to build their strengths and develop their weaknesses. Furthermore, organizations could use the typology to identify appropriate roles and responsibilities of managers for their specific needs. Consequently, this research is a valuable tool for understanding health care managerial behaviors that lead to improved decision making. At the same time, this could enhance satisfaction and performance and enable organizations to gain the competitive edge . ^

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A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^

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Men, particularly minorities, have higher rates of diabetes as compared with their counterparts. Ongoing diabetes self-management education and support by specialists are essential components to prevent the risk of complications such as kidney disease, cardiovascular diseases, and neurological impairments. Diabetes self-management behaviors, in particular, as diet and physical activity, have been associated with glycemic control in the literature. Recommended medical care for diabetes may differ by race/ethnicity. This study examined data from the National Health and Nutrition Examination Surveys, 2007 to 2010 for men with diabetes (N = 646) from four racial/ethnic groups: Mexican Americans, other Hispanics, non-Hispanic Blacks, and non-Hispanic Whites. Men with adequate dietary fiber intake had higher odds of glycemic control (odds ratio = 4.31, confidence interval [1.82, 10.20]), independent of race/ethnicity. There were racial/ethnic differences in reporting seeing a diabetes specialist. Non-Hispanic Blacks had the highest odds of reporting ever seeing a diabetes specialist (84.9%) followed by White non-Hispanics (74.7%), whereas Hispanics reported the lowest proportions (55.2% Mexican Americans and 62.1% other Hispanics). Men seeing a diabetes specialist had the lowest odds of glycemic control (odds ratio = 0.54, confidence interval [0.30, 0.96]). The results of this study suggest that diabetes education counseling may be selectively given to patients who are not in glycemic control. These findings indicate the need for examining referral systems and quality of diabetes care. Future studies should assess the effectiveness of patient-centered medical care provided by a diabetes specialist with consideration of sociodemographics, in particular, race/ethnicity and gender.