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Leveraging Generative AI Models for Synthetic Data Generation in Healthcare: Balancing Research and Privacy. (arXiv:2305.05247v1 [cs.LG])
cs.CR updates on arXiv.org arxiv.org
The widespread adoption of electronic health records and digital healthcare
data has created a demand for data-driven insights to enhance patient outcomes,
diagnostics, and treatments. However, using real patient data presents privacy
and regulatory challenges, including compliance with HIPAA and GDPR. Synthetic
data generation, using generative AI models like GANs and VAEs offers a
promising solution to balance valuable data access and patient privacy
protection. In this paper, we examine generative AI models for creating
realistic, anonymized patient data for …
adoption ai models challenges compliance data data-driven demand digital electronic health records gdpr generative generative ai health healthcare healthcare data hipaa insights outcomes privacy regulatory research synthetic synthetic data