Three LLMs generate clinically coherent, lexically diverse, and privacy-preserving synthetic mental health reports conditioned on ICD-10 codes, expanding usable training data for clinical NLP.
Textdataaugmentationforlargelanguagemodels: Acomprehensivesurveyofmethods,challenges, and opportunities
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Fidelity, Diversity, and Privacy: A Multi-Dimensional LLM Evaluation for Clinical Data Augmentation
Three LLMs generate clinically coherent, lexically diverse, and privacy-preserving synthetic mental health reports conditioned on ICD-10 codes, expanding usable training data for clinical NLP.