Data, Volume 7, Issue 12
2022 December - 16 articles
Cover Story: Clinical data analysis could lead to breakthroughs. However, clinical data contain sensitive information about participants that could be utilized for unethical activities, such as blackmailing, identity theft, mass surveillance, or social engineering. Data anonymization is a standard step during data collection, before sharing, to overcome the risk of disclosure. However, conventional data anonymization techniques could be more foolproof and could also hinder the opportunity for personalized evaluations. This paper establishes data standards derived from the original data set based on the utilities and quality of information and measures variations in the synthetic data set to evaluate the performance of the data synthesis process. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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