Assessing the fidelity of synthetic relational databases with high-dimensional categorical data: Proposal of a scalable visual framework.
- DOI
- 10.1016/j.ijmedinf.2026.106711
- Published
- 2026 Sep 3
- Container
- International journal of medical informatics
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.ijmedinf.2026.106711,
title = {Assessing the fidelity of synthetic relational databases with high-dimensional categorical data: Proposal of a scalable visual framework.},
author = {Girault R and Bensafir J and Lamer A and Beuscart JB and Génin M and Niang AT and Hammadi S and Chazard E},
year = {2026},
journal = {International journal of medical informatics},
doi = {10.1016/j.ijmedinf.2026.106711},
url = {https://doi.org/10.1016/j.ijmedinf.2026.106711}
}RIS
TY - JOUR TI - Assessing the fidelity of synthetic relational databases with high-dimensional categorical data: Proposal of a scalable visual framework. AU - Girault R AU - Bensafir J AU - Lamer A AU - Beuscart JB AU - Génin M AU - Niang AT AU - Hammadi S AU - Chazard E PY - 2026 JO - International journal of medical informatics DO - 10.1016/j.ijmedinf.2026.106711 UR - https://doi.org/10.1016/j.ijmedinf.2026.106711 ER -
APA
R, G., J, B., A, L., JB, B., M, G., AT, N., S, H., & E, C. (2026). Assessing the fidelity of synthetic relational databases with high-dimensional categorical data: Proposal of a scalable visual framework.. International journal of medical informatics. https://doi.org/10.1016/j.ijmedinf.2026.106711
Source records
- pubmed · retrieved 2026-09-26T03:05:55.844Z