Automated candidate confounder scoping for adjustment in clinical research: a retrieval-augmented generation approach

Jingjing Li1, Kesong Wu2, Xiao Wang3

  • 1Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, 545006, China.

Biodata Mining
|May 16, 2026
PubMed
Summary

This study introduces a local, abstract-only Retrieval-Augmented Generation (RAG) tool to identify potential confounding variables for observational studies. The system efficiently generates traceable confounder lists from PICO queries, aiding research design with privacy and cost considerations.

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