Algorithms on regulatory lockdown in medicine-Reference-Cited by-同舟云学术

Algorithms on regulatory lockdown in medicine

Published:2019-12-06 Issue:6470 Volume:366 Page:1202-1204
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Babic Boris¹,Gerke Sara²,Evgeniou Theodoros¹,Cohen I. Glenn³

Affiliation:

1. INSEAD, Singapore and Fontainebleau, France.

2. The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School; The Project on Precision Medicine, Artificial Intelligence, and the Law, Cambridge, MA, USA.

3. Harvard Law School, Cambridge, MA, USA.

Abstract

Prioritize risk monitoring to address the “update problem”

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference14 articles.

1. U.S. Food and Drug Administration (FDA) “Proposed regulatory framework for modifications to artificial intelligence/machine learning (AI/ML)-based software as a medical device (SaMD)” (discussion paper and request for feedback 2019); www.fda.gov/media/122535/download.

2. U.S. Food and Drug Administration (FDA) “Developing a Software Precertification Program: A Working Model ” (v.1.0 January 2019); www.fda.gov/media/119722/download.

3. The learning healthcare project “Background learning healthcare system” (2019); www.learninghealthcareproject.org/section/background/learning-healthcare-system.

4. A. Yala, C. Lehman, T. Schuster, T. Portnoi, R. Barzilay, Radiology 292, 60 (2019).

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