Data for A method for machine learning generation of realistic synthetic datasets for validating healthcare applications
- DOI
- 10.82444/warw.33837940.v1
- Published
- 2026
- Container
- Not recorded
- Publisher
- University of Warwick
- Open access
- yes
Credibility signals
limited evidence Score 47/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.82444/warw.33837940.v1,
title = {Data for A method for machine learning generation of realistic synthetic datasets for validating healthcare applications},
author = {Theodoros N. Arvanitis and Sean White and Stuart Harrison and Rupert Chaplin and George Despotou},
year = {2026},
doi = {10.82444/warw.33837940.v1},
url = {https://doi.org/10.82444/warw.33837940.v1}
}RIS
TY - JOUR TI - Data for A method for machine learning generation of realistic synthetic datasets for validating healthcare applications AU - Theodoros N. Arvanitis AU - Sean White AU - Stuart Harrison AU - Rupert Chaplin AU - George Despotou PY - 2026 DO - 10.82444/warw.33837940.v1 UR - https://doi.org/10.82444/warw.33837940.v1 ER -
APA
Arvanitis, T. N., White, S., Harrison, S., Chaplin, R., & Despotou, G. (2026). Data for A method for machine learning generation of realistic synthetic datasets for validating healthcare applications. https://doi.org/10.82444/warw.33837940.v1
Source records
- datacite · retrieved 2026-09-25T05:06:46.658Z