Regulation of clinical Artificial Intelligence (AI) in the Age of Agents: Unconfined Non-Deterministic Clinical Software (UNDCS) systems for healthcare

In a recent article, Weissman et al.<sup>1</sup> 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 devices<sup>1</sup> 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.

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Publication Details

Journal
npj Digital Medicine
Published
2026-02-23
DOI
https://doi.org/10.1038/s41746-026-02420-z
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Regulation of clinical Artificial Intelligence (AI) in the Age of Agents: Unconfined Non-Deterministic Clinical Software (UNDCS) systems for healthcare

C. C. Terence Tan, Danella Yaoxin Foo, Cheng Ooi Low, Dinesh Visva Gunasekeran et al.
npj Digital Medicine
Artificial Intelligence in Healthcare and Education
article

Regulation of clinical Artificial Intelligence (AI) in the Age of Agents: Unconfined Non-Deterministic Clinical Software (UNDCS) systems for healthcare

C. C. Terence Tan, Danella Yaoxin Foo, Cheng Ooi Low, Dinesh Visva Gunasekeran, Gabrielle Sze Yee Sim, Robert J. T. Morris, Tien Yin Wong
article en

Abstract

In a recent article, Weissman et al.<sup>1</sup> 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 devices<sup>1</sup> 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.

npj Digital MedicineVol. 9(1)
Ministry of Health (SG), National University of Singapore (SG), Nanyang Technological University (SG), Singapore National Eye Center (SG), Standards, Productivity and Innovation Board (SG), James Cook University Singapore (SG), Singapore Eye Research Institute (SG), Duke-NUS Medical School (SG), National University Hospital (SG), MOH Holdings (SG), Tsinghua University (CN)
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Openalex Percentile: Top 48%
Artificial Intelligence in Healthcare and Education
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