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arxiv: 2403.19511 · v1 · pith:V4NMFC7Bnew · submitted 2024-03-28 · 💻 cs.CL

Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data

classification 💻 cs.CL
keywords clinicaldatalanguagemodelsperformancesyntheticadvancedapplications
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Generative models have been showing potential for producing data in mass. This study explores the enhancement of clinical natural language processing performance by utilizing synthetic data generated from advanced language models. Promising results show feasible applications in such a high-stakes domain.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. CLR-voyance: Reinforcing Open-Ended Reasoning for Inpatient Clinical Decision Support with Outcome-Aware Rubrics

    cs.CL 2026-05 unverdicted novelty 6.0

    CLR-voyance reformulates inpatient reasoning as POMDP with clinician-validated outcome rubrics, yielding an 8B model that outperforms larger frontier models on the authors' new benchmark.