AI RESEARCH
Retrieval-Reasoning Large Language Model-based Synthetic Clinical Trial Generation
arXiv CS.LG
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ArXi:2410.12476v3 Announce Type: replace-cross Machine learning (ML) holds great promise for clinical applications but is often hindered by limited access to high-quality data due to privacy concerns, high costs, and long timelines associated with clinical trials. While large language models (LLMs) have nstrated strong performance in general-purpose generation tasks, their application to synthesizing realistic clinical trials remains underexplored.