Anonymizing Health Data
7
%
786 Kč 848 Kč
Sleva až 70% u třetiny knih
With this practical book, you will learn proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets.
| Autor: | El Emam, Khaled; Arbuckle, Luk |
| Nakladatel: | O'Reilly Media, Inc, USA |
| ISBN: | 9781449363079 |
| Rok vydání: | 2013 |
| Jazyk : | Angličtina |
| Vazba: | Paperback |
| Počet stran: | 150 |
Mohlo by se vám také líbit..
-
Practical Synthetic Data Generation
El Emam, Khaled; Arbuckle, Luk
-
Make: Analog Synthesizers
Wilson, Ray
-
Effective Modern C++
Meyers Scott
-
US For Beginners
Marsh, Joel
-
Java 8 Lambdas
Warburton, Richard
-
Theory of Fun for Game Design
Koster, Raph
-
Advanced Analytics with Spark
Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills
-
Learning Agile
Stellman, Andrew
-
Cloud Native Java
Gary Mak, Daniel Rubio, Josh Long
-
CSS Pocket Reference
Meyer Eric A.
-
JSON at Work
Marrs, Tom
-
Site Reliability Engineering
BETSY BEYER
-
Practical JIRA Administration
Doar, Matthew B.
-
Building Products for the Enterprise
Reeves, Blair; Gaines, Benjamin
-
The Manager`s Path
Camille Fournier
-
macOS Mojave: The Missing Manual
Pogue, David
