Towards Fair and Efficient De-identification: Quantifying the Efficiency and Generalizability of De-identification Approaches
arXiv:2602.15869v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on clinical de-identification, the task of identifying sensitive identifiers to protect privacy. …
Noopur Zambare, Kiana Aghakasiri, Carissa Lin, Carrie Ye, J. Ross Mitchell, Mohamed Abdalla
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