Imperial College London
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ProfessorNicholasPeters

Faculty of Medicine, National Heart & Lung Institute

Professor of Cardiac Electrophysiology
 
 
 
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Contact

 

+44 (0)20 7594 1880n.peters Website

 
 
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Assistant

 

Ms Anastasija Schmidt +44 (0)20 7594 1880

 
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Location

 

NHLI officesSir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Mashar:2023:10.2196/42940,
author = {Mashar, M and Chawla, S and Chen, F and Lubwama, B and Patel, K and Kelshiker, MA and Bachtiger, P and Peters, NS},
doi = {10.2196/42940},
journal = {JMIR AI},
pages = {e42940--e42940},
title = {Artificial Intelligence Algorithms in Health Care: Is the Current Food and Drug Administration Regulation Sufficient?},
url = {http://dx.doi.org/10.2196/42940},
volume = {2},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:p>Given the growing use of machine learning (ML) technologies in health care, regulatory bodies face unique challenges in governing their clinical use. Under the regulatory framework of the Food and Drug Administration, approved ML algorithms are practically locked, preventing their adaptation in the ever-changing clinical environment, defeating the unique adaptive trait of ML technology in learning from real-world feedback. At the same time, regulations must enforce a strict level of patient safety to mitigate risk at a systemic level. Given that ML algorithms often support, or at times replace, the role of medical professionals, we have proposed a novel regulatory pathway analogous to the regulation of medical professionals, encompassing the life cycle of an algorithm from inception, development to clinical implementation, and continual clinical adaptation. We then discuss in-depth technical and nontechnical challenges to its implementation and offer potential solutions to unleash the full potential of ML technology in health care while ensuring quality, equity, and safety. References for this article were identified through searches of PubMed with the search terms “Artificial intelligence,” “Machine learning,” and “regulation” from June 25, 2017, until June 25, 2022. Articles were also identified through searches of the reference list of the articles. Only papers published in English were reviewed. The final reference list was generated based on originality and relevance to the broad scope of this paper.</jats:p>
AU  - Mashar,M
AU  - Chawla,S
AU  - Chen,F
AU  - Lubwama,B
AU  - Patel,K
AU  - Kelshiker,MA
AU  - Bachtiger,P
AU  - Peters,NS
DO  - 10.2196/42940
EP  - 42940
PY  - 2023///
SP  - 42940
TI  - Artificial Intelligence Algorithms in Health Care: Is the Current Food and Drug Administration Regulation Sufficient?
T2  - JMIR AI
UR  - http://dx.doi.org/10.2196/42940
VL  - 2
ER  -
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