1.0Transdisciplinary Research Lab on IT Ecosystemshttps://latece.uqam.ca/en/Synthetic Data Anonymity - Transdisciplinary Research Lab on IT Ecosystems - UQAMrich600338<blockquote class="wp-embedded-content" data-secret="GN1eyk4Dy2"><a href="https://latece.uqam.ca/en/projects/anonymite-des-donnees-synthetiques/">Synthetic Data Anonymity</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://latece.uqam.ca/en/projects/anonymite-des-donnees-synthetiques/embed/#?secret=GN1eyk4Dy2" width="600" height="338" title="“Synthetic Data Anonymity” — Transdisciplinary Research Lab on IT Ecosystems" data-secret="GN1eyk4Dy2" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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Assessing the residual privacy risks of synthetic data In the field of medical research, and in relation to knowledge development more broadly, machine learning models can now be trained to generate synthetic (fictitious) patient profiles using real patient data. How can we characterize the residual privacy risks of these synthetic profiles? LATECE domain Connected health […]https://latece.uqam.ca/wp-content/uploads/2026/04/TuileTest_Gambs3_ENG.png10801080