privacy

December 21, 2022

EHR-Safe: Generating High-Fidelity and Privacy-Preserving Synthetic Electronic Health Records

Posted by Jinsung Yoon and Sercan O. Arik, Research Scientists, Google Research, Cloud AI Team Analysis of Electronic Health Records (EHR) has a tremendous potential for enhancing patient care, quantitatively measuring performance of clinical practices, and facilitating clinical research. Statistical estimation and machine learning (ML) models trained on EHR data can be used to predict…

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Differential Privacy Accounting by Connecting the Dots
December 20, 2022

Differential Privacy Accounting by Connecting the Dots

Posted by Pritish Kamath and Pasin Manurangsi, Research Scientists, Google Research Differential privacy (DP) is an approach that enables data analytics and machine learning (ML) with a mathematical guarantee on the privacy of user data. DP quantifies the “privacy cost” of an algorithm, i.e., the level of guarantee that the algorithm’s output distribution for a…

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