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Synthetic data generation for tabular health records: A systematic review
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“Various methods and evaluation metrics are used to assess the privacy dimension of the synthetic tabular data generation approaches. These methods include identity disclosure, attribute disclosure, distance to the closest record, membership attack, maximum real-to-synthetic similarity, differential privacy cost, and GANs.”
From Generative AI in medical practice: in-depth exploration of privacy and security challenges (2024) · cites this paper as [47]
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“Hernandez et al [47] discuss privacy concerns related to synthetic tabular data generation in health care.”
From Generative AI in medical practice: in-depth exploration of privacy and security challenges (2024) · cites this paper as [47]
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Wang, N., Lu, Y., Treewaree, S., Zirikly, A., Nguyen, M., Agarwal, B., Shah, J., Stevenson, J., & Taylor, C. O. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4872174
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Retracted
Metadata
- Authors
- Hernandez, M., Epelde, G., Alberdi, A., Cilla, R., & Rankin, D.
- Affiliations
- Vicomtech (ES)
- Mondragon Unibertsitatea (ES)
- University of Ulster (GB)
- Corresponding author
- Hernandez, Mikel
- Epelde, Gorka
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2022-07
- Volume
- 493
- Pages
- 28-45
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W4224022798
- Cited by
- 278
- References
- 60
- Citations by year
- 2026: 56 · 2025: 90 · 2024: 88 · 2023: 36 · 2022: 8
- FWCI
- 3.87
- Type
- journal article
- Language
- en
- Open access
- green
- pure.ulster.ac.uk
- Licence
- Locations
- Neurocomputing (publishedVersion)
- Ulster University Research Portal (Ulster University) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- synthetic data generation, tabular data generation, healthcare data privacy, generative adversarial networks, synthetic tabular data generation, patient privacy
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