Fatma Sumeyra Dogan* , & EL MESTARI, S. Z.*. (In press). Techniques to achieve anonymization of health data: When are they sufficient to be considered as legally complaint? Springer Communications in Computer and Information Science. Peer reviewed * These authors have contributed equally to this work. |
Poe, R. L., & EL MESTARI, S. Z. (2024). The Conflict Between Algorithmic Fairness and Non-Discrimination: An Analysis of Fair Automated Hiring. Journal of the Association for Computing Machinery. doi:10.1145/3630106.3659015 Peer Reviewed verified by ORBi |
EL MESTARI, S. Z., LENZINI, G., & DEMIRCI, H. (February 2024). Preserving data privacy in machine learning systems. Computers and Security, 137, 103605. doi:10.1016/j.cose.2023.103605 Peer Reviewed verified by ORBi |
EL MESTARI, S. Z.* , Doğan, F. S.* , & Maria Botes, W. (2023). Technical and Legal Aspects Relating to the (Re)Use of Health Data When Repurposing Machine Learning Models in the EU. In Privacy Symposium 2023 (pp. 33--48). Springer International Publishing. doi:10.1007/978-3-031-44939-0_3 Peer reviewed * These authors have contributed equally to this work. |