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Privacy preserving data publishing of categorical data through k-anonymity and feature selection
In healthcare, there is a vast amount of patients’ data, which can lead to important discoveries if combined. Due to legal and ethical issues, such data cannot be shared and hence such information is underused. A new area of research has emerged, called privacy preserving data publishing (PPDP), whi...
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| 出版年: | Healthc Technol Lett |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
The Institution of Engineering and Technology
2016
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4814843/ https://ncbi.nlm.nih.gov/pubmed/27222728 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1049/htl.2015.0050 |
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