SynthCheck: A Dashboard for Synthetic Data Quality Assessment

Gabriele Santangelo, Giovanna Nicora, Riccardo Bellazzi, Arianna Dagliati

2024

Abstract

In recent years, synthetic data generation has become a topic of growing interest, especially in healthcare, where they can support the development of robust Artificial Intelligence (AI) tools. Additionally, synthetic data offer advantages such as easier sharing and consultation compared to original data, which are subject to patient privacy laws that have become increasingly rigorous in recent years. To ensure a safe use of synthetic data, it is necessary to assess their quality. Synthetic data quality evaluation is based on three properties: resemblance, utility, and privacy, that can be measured using different statistical approaches. Automatic evaluation of synthetic data quality can foster their safe usage within medical AI systems. For this reason, we have developed a dashboard application, in which users can perform a comprehensive quality assessment of their synthetic data. This is achieved through a user-friendly interface, providing easy access and intuitive functionalities for generating reports.

Paper Citation

in Harvard Style

Santangelo G., Nicora G., Bellazzi R. and Dagliati A. (2024). SynthCheck: A Dashboard for Synthetic Data Quality Assessment. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 246-256. DOI: 10.5220/0012558700003657

in Bibtex Style

@conference{healthinf24,
author={Gabriele Santangelo and Giovanna Nicora and Riccardo Bellazzi and Arianna Dagliati},
title={SynthCheck: A Dashboard for Synthetic Data Quality Assessment},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={246-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012558700003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - SynthCheck: A Dashboard for Synthetic Data Quality Assessment
SN - 978-989-758-688-0
AU - Santangelo G.
AU - Nicora G.
AU - Bellazzi R.
AU - Dagliati A.
PY - 2024
SP - 246
EP - 256
DO - 10.5220/0012558700003657
PB - SciTePress