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"With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost efficient manner.Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions."

"This book constitutes the refereed and revised proceedings of the workshops and the doctoral consortium co-located with the 10th International Conference on Perspectives in Business Informatics Research (BIR), held in Riga, Latvia, in October 2011. The four workshops focused on Information Logistics and Knowledge Supply for Viable Enterprises (ILOG 2011), Alignment of Business Processes and Security Modeling (ABPSM 2011), Intelligent Educational Systems and Technology-Enhanced Learning (INTEL-EDU 2011), and User-Oriented Information Integration (UOII 2011). The two best papers from the doctoral consortium are also included."