FD-NL2SQL: Feedback-Driven Clinical NL2SQL that Improves with Use
Clinicians exploring oncology trial repositories often need ad-hoc, multi-constraint queries over biomarkers, endpoints, interventions, and time, yet writing SQL requires schema expertise. We demo FD-NL2SQL, a feedback-driven clinical NL2SQL assistant for SQLite-based oncology databases. Given a natural-language question, a schema-aware LLM decomposes it into predicate-level sub-questions, retrieves semantically similar expert-verified NL2SQL exemplars via sentence embeddings, and synthesizes executable SQL conditioned on the decomposition, retrieved exemplars, and schema, with post-processing validity checks. To improve with use, FD-NL2SQL incorporates two update signals: (i) clinician e...
| Authors | Suparno Roy Chowdhury, Tejas Anvekar, Manan Roy Choudhury et al. |
|---|---|
| Primary category | cs.CL |
| Published | 17 April 2026 |
| Last updated at source | 17 April 2026 |
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