Privacy preserving strategies for electronic health records in the era of large language models.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 39820020.
- Also identified by DOI 10.1038/s41746-025-01429-0 and PMC identifier 11739470.
- Licence recorded as CC BY-NC-ND.
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Abstract
Electronic health records (EHRs) secondary usage with large language models (LLMs) raise privacy challenges. National regulations like GDPR and HIPAA offer protection frameworks, but specific strategies are needed to mitigate risk in generative AI. Risks can be reduced by using strategies like privacy-preserving locally deployed LLMs, synthetic data generation, differential privacy, and deidentification. Depending on the task, strategies should be employed to increase compliance with patient privacy regulatory frameworks.