The application of differential privacy to health data

134 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing (2014, positive): “Dankar and Emam [10] discuss the use of differential privacy in medical applications, pointing out the various tradeoffs between interactive and noninteractive mechanisms and the limitation of utility guarantees in differential privacy, but do not study its use in any specific medical applications.”
The optimal mechanism in differential privacy (2012, unknown): “, [10], [11], [12], [13], [14], [5], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46].”
Machine learning and genomics: precision medicine versus patient privacy (2018, background): “There is still a strong need for mechanisms for releasing a noisy version of the data, on which one can efficiently get highly accurate answers from a variety of queries [43].”