LLM-rephrased synthetic clinical notes preserve core information and utility for coarse prediction tasks but lose fine-grained details such as ICD codes, with chunk-wise rephrasing as a partial mitigation that trades off factual accuracy.
Verifying facts in patient care documents generated by large language models using electronic health records
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Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note Scale
LLM-rephrased synthetic clinical notes preserve core information and utility for coarse prediction tasks but lose fine-grained details such as ICD codes, with chunk-wise rephrasing as a partial mitigation that trades off factual accuracy.