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Optimizing an LLM-Based Clinical Data Querying System Using Metadata Enrichment and Task Decomposition

2025-12-23 health informatics Title + abstract only
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Accessing complex clinical registries traditionally requires SQL programming expertise, limiting data accessibility for non-technical researchers. In this paper, we designed and evaluated whether a text-to-SQL solution based on large language models (LLMs) could enable natural language querying of a real-world clinical registry under strict privacy and security constraints. Using self-hosted, open-source LLMs, we developed a multi-layered optimization framework incorporating metadata enrichment,...

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