AI-Driven Synthetic Health Data Generation for Secure Cloud-Based System Testing and Data Augmentation

Authors

  • Ashwini Pankaj Mahajan

Keywords:

Synthetic Health Data Generation, Differential Privacy, Generative Adversarial Networks, Healthcare Machine Learning, Cloud-Based System Testing

Abstract

The healthcare industry is faced with the twofold challenge of using massive stores of medicalinformation to spur innovation, and protecting patient privacy against the growing number of privacythreats and increasingly complex regulatory policies. The creation of synthetic health data using state-of the-art artificial intelligence models

References

Jordan Zheng Ting Sim, et al., "Machine learning in medicine: what clinicians should know," PubMed Central, 2021. [Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC10071847/

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Published

2026-01-08

How to Cite

Ashwini Pankaj Mahajan. (2026). AI-Driven Synthetic Health Data Generation for Secure Cloud-Based System Testing and Data Augmentation . Journal of Computational Analysis and Applications (JoCAAA), 35(1), 170–180. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4652

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Section

Articles