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人工智能驱动的软件作为医疗器械监管的全球协调:应对挑战与统一标准。

Global Harmonization of Artificial Intelligence-Enabled Software as a Medical Device Regulation: Addressing Challenges and Unifying Standards.

作者信息

Reddy Sandeep

机构信息

Health Management and Leadership Discipline, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, Queensland.

出版信息

Mayo Clin Proc Digit Health. 2024 Dec 24;3(1):100191. doi: 10.1016/j.mcpdig.2024.100191. eCollection 2025 Mar.


DOI:10.1016/j.mcpdig.2024.100191
PMID:40207007
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11975980/
Abstract

The growing incorporation of artificial intelligence (AI) into medical device software offers substantial prospects and regulatory hurdles. As AI software as a medical device (AI-SaMD) continues to advance, ensuring its safety, effectiveness, and security is paramount. Nevertheless, the regulatory environment needs more cohesion, with various regions implementing diverse strategies. This paper underscores the necessity for globally harmonized AI-SaMD regulations by examining key regulatory frameworks from the United States, the European Union, China, and Australia. The article also explores crucial elements for harmonization, including algorithm transparency, risk management, data security, and clinical evaluation. Furthermore, the paper advocates for implementing international standards and global data security protocols, emphasizing the significance of cross-border cooperation to ensure the worldwide safety and efficacy of AI-SaMD.

摘要

将人工智能(AI)纳入医疗设备软件的趋势日益明显,这既带来了巨大的前景,也带来了监管方面的障碍。随着作为医疗设备的人工智能软件(AI-SaMD)不断发展,确保其安全性、有效性和安全性至关重要。然而,监管环境需要更强的一致性,因为不同地区实施的策略各不相同。本文通过审视美国、欧盟、中国和澳大利亚的关键监管框架,强调了全球统一的AI-SaMD法规的必要性。文章还探讨了协调的关键要素,包括算法透明度、风险管理、数据安全和临床评估。此外,本文主张实施国际标准和全球数据安全协议,强调跨境合作对于确保AI-SaMD在全球范围内的安全性和有效性的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72ea/11975980/8cf191797a72/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72ea/11975980/8cf191797a72/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72ea/11975980/8cf191797a72/gr1.jpg

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[2]
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引用本文的文献

[1]
Artificial Intelligence in Aesthetic Medicine: Applications, Challenges, and Future Directions.

J Cosmet Dermatol. 2025-6

[2]
The Transformative Role of Artificial Intelligence in Plastic and Reconstructive Surgery: Challenges and Opportunities.

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本文引用的文献

[1]
The Evolving Regulatory Paradigm of AI in MedTech: A Review of Perspectives and Where We Are Today.

Ther Innov Regul Sci. 2024-5

[2]
Generative AI in healthcare: an implementation science informed translational path on application, integration and governance.

Implement Sci. 2024-3-15

[3]
Global Regulatory Frameworks for the Use of Artificial Intelligence (AI) in the Healthcare Services Sector.

Healthcare (Basel). 2024-2-28

[4]
Navigating the AI Revolution: The Case for Precise Regulation in Health Care.

J Med Internet Res. 2023-9-11

[5]
The Challenges of Regulating Artificial Intelligence in Healthcare Comment on "Clinical Decision Support and New Regulatory Frameworks for Medical Devices: Are We Ready for It? - A Viewpoint Paper".

Int J Health Policy Manag. 2023

[6]
Conceptual and normative approaches to AI governance for a global digital ecosystem supportive of the UN Sustainable Development Goals (SDGs).

AI Ethics. 2022

[7]
The need for a system view to regulate artificial intelligence/machine learning-based software as medical device.

NPJ Digit Med. 2020-4-7

[8]
Key challenges for delivering clinical impact with artificial intelligence.

BMC Med. 2019-10-29

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