¶ … healthcare model that could enable physicians determine their patients' susceptibility to future disease on the bases of their medical records, and most importantly, their similarity to other patients. They acknowledge that despite numerous studies indicating a shift from the traditional disease-based to the more effective patient-centered approach of healthcare delivery, there still exists a knowledge gap, particularly because of the lack of a computational tool that can effectively discover patients' disease patterns without "falling prey to the noise" (Chawla & Davis, 2013, p. 660). The authors put forth the CARE model, which they posit addresses these concerns better than the existing models. They base their development on a number of findings from exiting literature. The CARE model establishes risk factors by leveraging a patient's symptoms and traits with their interactions and biological disease information. To this end, its operation rides on the findings of a 2009 study by Schadt, which held that phenotypes are produced through molecular interactions, and that hence, molecular and genetic "data can be integrated with phenotypic...
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Zaslavsky is the leader of the Semantic Data Management Science Area (SMSA). He has published more than 300 publications on science and technology. Perera has vast experience in computing and technology as he is a member of the Commonwealth Scientific and Industrial Research Organization alongside publishing numerous journals. Georgakopoulos is the Director of Information Engineering Laboratory. He has published over 100 journals on issues related to science and technology
Figure 1 portrays the state of Maryland, the location for the focus of this DRP. Figure 1: Map of Maryland, the State (Google Maps, 2009) 1.3 Study Structure Organization of the Study The following five chapters constitute the body of Chapter I: Introduction Chapter II: Review of the Literature Chapter III: Methods and Results Chapter IV: Chapter V: Conclusions, Recommendations, and Implications Chapter I: Introduction During Chapter I, the researcher presents this study's focus, as it relates to the
Big Data Shopping Big data is a relatively recent concept in the marketing world, that describes the process of analyzing massive data sets to unearth trends. The data sets are so large that it would be almost impossible to find such trends without high-powered analytical technology. Big data has been facilitated by the ability to gather massive amounts of information about consumer profiles and shopping trends. The primarily facilitators of big
Peachtree Healthcare IT Architecture Recommendations to Peachtree Healthcare The discussions and cursory analyses in the Harvard Business Review case Too Far Ahead of the IT Curve? (Dalcher, 2005) attempt to implement massive IT projects without considering the implications from a strategic and tactical level. There is no mention of the most critical legal considerations of any healthcare provider, and this includes compliance to the Health Insurance Portability and Accountability Act of 1996
Others include delays in data accessibility, albeit shorter delays and the continued need for source data verification (Donovan, 2007). Other obstacles have occurred in the developing of mobile healthcare applications. These have included mobile device limitations, wireless networking problems, infrastructure constraints, security concerns, and user distrust (Keng and Shen, 2006). A third problem that has been encountered is that of a lack of education on not only the importance of the
1.3. Summary of argument, Hypothesis The role of leadership styles and their applicability to the success or failure of mergers, acquisitions and alliances is the focus of this research. Any leadership study, to be relevant, must also focus on the needs of those served by the organizations studies. That is why in the proposed Change Management Equilibrium Model have customer-driven processes at their center or core. The focus of the research
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