Peer-Reviewed Publication
PLOS Digit Health2022;1(5):e0000040.May 1, 2022Journal Article
A distributed approach to the regulation of clinical AI.
Trishan Panch1,2, Erin Duralde3, Heather Mattie4, Gopal Kotecha4, Leo Anthony Celi4,5,6, Melanie Wright7, Felix Greaves8,9
1Division of Health Policy and Management, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.
2Wellframe Inc., Boston, Massachusetts.
3Population Health Management, Mass General Brigham, Somerville, Massachusetts.
4Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.
5Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts.
6Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
7College of Pharmacy, Idaho State University, Meridian, Idaho.
8National Institute for Health and Care Excellence, London, United Kingdom.
9Imperial College, London, United Kingdom.
Abstract
Regulation is necessary to ensure the safety, efficacy and equitable impact of clinical artificial intelligence (AI). The number of applications of clinical AI is increasing, which, amplified by the need for adaptations to account for the heterogeneity of local health systems and inevitable data drift, creates a fundamental challenge for regulators. Our opinion is that, at scale, the incumbent mod…
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