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...chieved by either perturbing the sensitive attribute, perturbing attributes that serve as identification mechanisms, or a combination of the two. Clearly, this process required the reduction in the accuracy of data representation. Therefore, privacy preservation almost always incurs the cost of losing some data utility. Therefore, the goal of privacy preservation methods is to optimize the trade-off between utility and privacy. This ensures that the amount of utility loss at a given level of privacy is as little as possible. The major steps in privacy-preserving data publication algorithms [5][18] are the identification of an appropriate privacy metric and level for a given access setting and data characteristics, application of one or multiple privacy-preserving algorithm(s) to achieve the desired privacy level, and postanalyzing the utility of the processed data. These three steps are repeated until the desired utility and privacy levels are jointly met. Chapter 15 focuses on applying privacy-preserving algorithms to healthcare data for secondary-use data publishing and interpretation of the usefulness and implications of the processed data. 12 Healthcare Data Analytics 1.4 Applicati...

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...the statistical database literature. Privacy, especially in healthcare, should be interpreted from both systemic and information perspectives to clearly understand potential breaches and consequences =-=[75]-=-. 1.2 Current Practices and Limitations In recent years, both public and private sectors have released and published an incredible amount of data that were previously not accessible. For example, data...