Literature DB >> 33478929

Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.

Urs J Muehlematter1, Paola Daniore2, Kerstin N Vokinger3.   

Abstract

There has been a surge of interest in artificial intelligence and machine learning (AI/ML)-based medical devices. However, it is poorly understood how and which AI/ML-based medical devices have been approved in the USA and Europe. We searched governmental and non-governmental databases to identify 222 devices approved in the USA and 240 devices in Europe. The number of approved AI/ML-based devices has increased substantially since 2015, with many being approved for use in radiology. However, few were qualified as high-risk devices. Of the 124 AI/ML-based devices commonly approved in the USA and Europe, 80 were first approved in Europe. One possible reason for approval in Europe before the USA might be the potentially relatively less rigorous evaluation of medical devices in Europe. The substantial number of approved devices highlight the need to ensure rigorous regulation of these devices. Currently, there is no specific regulatory pathway for AI/ML-based medical devices in the USA or Europe. We recommend more transparency on how devices are regulated and approved to enable and improve public trust, efficacy, safety, and quality of AI/ML-based medical devices. A comprehensive, publicly accessible database with device details for Conformité Européene (CE)-marked medical devices in Europe and US Food and Drug Administration approved devices is needed.
Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Year:  2021        PMID: 33478929     DOI: 10.1016/S2589-7500(20)30292-2

Source DB:  PubMed          Journal:  Lancet Digit Health        ISSN: 2589-7500


  38 in total

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Journal:  BMJ Open       Date:  2022-05-17       Impact factor: 3.006

3.  User acceptance of wearable intelligent medical devices through a modified unified theory of acceptance and use of technology.

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Journal:  Circ Res       Date:  2022-02-17       Impact factor: 23.213

5.  An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research.

Authors:  Joe Zhang; Stephen Whebell; Jack Gallifant; Sanjay Budhdeo; Heather Mattie; Piyawat Lertvittayakumjorn; Maria Del Pilar Arias Lopez; Beatrice J Tiangco; Judy W Gichoya; Hutan Ashrafian; Leo A Celi; James T Teo
Journal:  Lancet Digit Health       Date:  2022-04

6.  Mitigating bias in machine learning for medicine.

Authors:  Kerstin N Vokinger; Stefan Feuerriegel; Aaron S Kesselheim
Journal:  Commun Med (Lond)       Date:  2021-08-23

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8.  Big data and predictive analytics in healthcare in Bangladesh: regulatory challenges.

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Journal:  Heliyon       Date:  2021-05-29

9.  Analysis and Comparison of Two Artificial Intelligence Diabetic Retinopathy Screening Algorithms in a Pilot Study: IDx-DR and Retinalyze.

Authors:  Andrzej Grzybowski; Piotr Brona
Journal:  J Clin Med       Date:  2021-05-27       Impact factor: 4.241

Review 10.  Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review.

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Journal:  JMIR Hum Factors       Date:  2021-06-18
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