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Mapping the regulatory landscape for artificial intelligence in health within the European Union.

作者信息

Schmidt Jelena, Schutte Nienke M, Buttigieg Stefan, Novillo-Ortiz David, Sutherland Eric, Anderson Michael, de Witte Bart, Peolsson Michael, Unim Brigid, Pavlova Milena, Stern Ariel Dora, Mossialos Elias, van Kessel Robin

机构信息

Department of International Health, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands.

Innovation in Health Information Systems Unit, SD Data Governance, Sciensano, Brussels, Belgium.

出版信息

NPJ Digit Med. 2024 Aug 27;7(1):229. doi: 10.1038/s41746-024-01221-6.


DOI:10.1038/s41746-024-01221-6
PMID:39191937
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11350181/
Abstract

Regulatory frameworks for artificial intelligence (AI) are needed to mitigate risks while ensuring the ethical, secure, and effective implementation of AI technology in healthcare and population health. In this article, we present a synthesis of 141 binding policies applicable to AI in healthcare and population health in the EU and 10 European countries. The EU AI Act sets the overall regulatory framework for AI, while other legislations set social, health, and human rights standards, address the safety of technologies and the implementation of innovation, and ensure the protection and safe use of data. Regulation specifically pertaining to AI is still nascent and scarce, though a combination of data, technology, innovation, and health and human rights policy has already formed a baseline regulatory framework for AI in health. Future work should explore specific regulatory challenges, especially with respect to AI medical devices, data protection, and data enablement.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/86163b558c3e/41746_2024_1221_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/a09a6433bdef/41746_2024_1221_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/9f3e8215eed6/41746_2024_1221_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/86163b558c3e/41746_2024_1221_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/a09a6433bdef/41746_2024_1221_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/9f3e8215eed6/41746_2024_1221_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8e/11350181/86163b558c3e/41746_2024_1221_Fig3_HTML.jpg

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本文引用的文献

[1]
EU-US data transfers: an enduring challenge for health research collaborations.

NPJ Digit Med. 2024-8-16

[2]
Core elements of national policy for digital health technology evidence and access.

NPJ Digit Med. 2024-8-13

[3]
Navigating the European Union Artificial Intelligence Act for Healthcare.

NPJ Digit Med. 2024-8-12

[4]
Exploring potential drivers of patient engagement with their health data through digital platforms: A scoping review.

Int J Med Inform. 2024-9

[5]
Advancing equity in medical device performance.

Lancet Glob Health. 2024-5

[6]
Offline: A mirage of progress for health and democracy.

Lancet. 2024-4-13

[7]
New AI regulation in the EU seeks to reduce risk without assessing public benefit.

Nat Med. 2024-5

[8]
Social and Behavioral Determinants of Health in the Era of Artificial Intelligence with Electronic Health Records: A Scoping Review.

Health Data Sci. 2021-8-24

[9]
Privacy-preserving federated machine learning on FAIR health data: A real-world application.

Comput Struct Biotechnol J. 2024-2-17

[10]
Large language models to identify social determinants of health in electronic health records.

NPJ Digit Med. 2024-1-11

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