In a recent article, Weissman et al.1 examined the extent to which artificial intelligence (AI)-based large language models (LLMs) generate clinical decision support (CDS) outputs that meet the criteria of regulated medical devices1 and called for new regulations for LLM-based CDS systems. In this manuscript, we respond to the proposed considerations highlighting those that have been addressed by existing guidelines and would not need new frameworks, as well as the need for new regulations of “generalized” CDSS that are not anchored to specific clinical indications. We contextualise this regulatory gap with an overview of the literature distinguishing between confined and unconfined AI systems. We also outline specific areas in which new regulations may be required, along with risk mitigation strategies that could be incorporated in new guidelines.
