Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation
Article
Article Title | Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation |
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ERA Journal ID | 5039 |
Article Category | Article |
Authors | Li, Yintong, Acharya, U. Rajendra and Tan, Jen Hong |
Journal Title | Computer Methods and Programs in Biomedicine |
Journal Citation | 260 |
Article Number | 108571 |
Number of Pages | 18 |
Year | 2025 |
Publisher | Elsevier |
ISSN | 0169-2607 |
1872-7565 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.cmpb.2024.108571 |
Web Address (URL) | https://www.sciencedirect.com/science/article/abs/pii/S0169260724005649 |
Abstract | Background: |
Keywords | Deep learning; Privacy preservation; Synthetic data generation; Healthcare data sharing; Generative Adversarial Networks (GANs) |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 420311. Health systems |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | National University of Singapore |
School of Mathematics, Physics and Computing | |
Centre for Health Research | |
Singapore General Hospital, Singapore |
https://research.usq.edu.au/item/zx0z8/preserving-privacy-in-healthcare-a-systematic-review-of-deep-learning-approaches-for-synthetic-data-generation
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