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arXiv Computation and Language By Nikkie Hooman, Monarch Nigam, Amy E. Hughes, Rasmi G. Nair, Mehak Gupta

VERGE: Verification-Enhanced Refinement for Grounded Extraction of Early-Onset Colorectal Cancer Symptoms in Clinical Notes

Read the original on arXiv Computation and Language →

The paper introduces VERGE, a verification-enhanced refinement workflow that extracts six red‑flag symptoms and family‑history risk status for early‑onset colorectal cancer from free‑text clinical notes. VERGE uses retrieval‑augmented generation followed by a bounded verification‑refinement cycle that checks textual grounding and clinical validity, correcting claims until resolved or escalating to human review. In evaluation on 4,033 clinician‑labeled note‑finding pairs, VERGE improved precision from 0.764 to 0.849 and MCC from 0.681 to 0.730 compared to a single‑agent baseline, while requiring human review for only 1.5 % of claims.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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