CLOVER: A framework for benchmarking synthetic data generation methods balancing utility and privacy in healthcare
- DOI
- 10.1016/j.ailsci.2026.100155
- Published
- 06
- Container
- Artificial Intelligence in the Life Sciences
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.ailsci.2026.100155,
title = {CLOVER: A framework for benchmarking synthetic data generation methods balancing utility and privacy in healthcare},
author = {Yue Qi and Lorrie Herbault and Hadrien Lautraite and Michael Yu and Katleen Blanchet and Christian Vincelette and Louis Mullie and Guillaume Dumas and Jean-François Rajotte and Kamran Afzali and Sébastien Gambs and Michaël Chassé},
year = {2026},
journal = {Artificial Intelligence in the Life Sciences},
doi = {10.1016/j.ailsci.2026.100155},
url = {https://doi.org/10.1016/j.ailsci.2026.100155}
}RIS
TY - JOUR TI - CLOVER: A framework for benchmarking synthetic data generation methods balancing utility and privacy in healthcare AU - Yue Qi AU - Lorrie Herbault AU - Hadrien Lautraite AU - Michael Yu AU - Katleen Blanchet AU - Christian Vincelette AU - Louis Mullie AU - Guillaume Dumas AU - Jean-François Rajotte AU - Kamran Afzali AU - Sébastien Gambs AU - Michaël Chassé PY - 2026 JO - Artificial Intelligence in the Life Sciences DO - 10.1016/j.ailsci.2026.100155 UR - https://doi.org/10.1016/j.ailsci.2026.100155 ER -
APA
Qi, Y., Herbault, L., Lautraite, H., Yu, M., Blanchet, K., Vincelette, C., Mullie, L., Dumas, G., Rajotte, J., Afzali, K., Gambs, S., & Chassé, M. (2026). CLOVER: A framework for benchmarking synthetic data generation methods balancing utility and privacy in healthcare. Artificial Intelligence in the Life Sciences. https://doi.org/10.1016/j.ailsci.2026.100155
Source records
- doaj · retrieved 2026-09-26T04:42:33.245Z