Reply to ensuring trustworthy AI assisted guideline development for clinical practice.
Where this comes from
- Record sourced from PubMed, PMID 42661029.
- Also identified by DOI 10.1038/s41746-026-03099-y.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
In this Reply, we respond to the Matters Arising by Zhang and Fu regarding the trustworthiness of AI-assisted clinical guideline development, using Quicker as a case study. We clarify which safeguards for transparency, traceability, and uncertainty handling are already embedded, to a substantial extent, in Quicker's design, and outline areas of alignment on validation, governance, and modular evaluation. We further discuss broader challenges related to trust, safeguards, and responsible deployment of large language model-based systems in evidence-based medicine. We emphasize that advancing such systems requires not only technical acceleration, but also systematic human oversight, rigorous evaluation frameworks, and community-wide governance to ensure safe and trustworthy clinical adoption.