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Regulatory responses to medical machine learning.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Minssen, Timo 
Gerke, Sara 
Price, Nicholson 
Cohen, Glenn 

Abstract

Companies and healthcare providers are developing and implementing new applications of medical artificial intelligence, including the artificial intelligence sub-type of medical machine learning (MML). MML is based on the application of machine learning (ML) algorithms to automatically identify patterns and act on medical data to guide clinical decisions. MML poses challenges and raises important questions, including (1) How will regulators evaluate MML-based medical devices to ensure their safety and effectiveness? and (2) What additional MML considerations should be taken into account in the international context? To address these questions, we analyze the current regulatory approaches to MML in the USA and Europe. We then examine international perspectives and broader implications, discussing considerations such as data privacy, exportation, explanation, training set bias, contextual bias, and trade secrecy.

Description

Keywords

artificial intelligence, ethics, medical devices, medical machine learning, regulation

Journal Title

J Law Biosci

Conference Name

Journal ISSN

2053-9711
2053-9711

Volume Title

7

Publisher

Oxford University Press (OUP)
Sponsorship
Novo Nordisk Foundation (via University of Copenhagen) (NNF17SA0027784)