Machine learning in medicine: Addressing ethical challenges

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.

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Bibliographic Details
Published inPLoS medicine Vol. 15; no. 11; p. e1002689
Main Authors Vayena, Effy, Blasimme, Alessandro, Cohen, I Glenn
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 06.11.2018
Public Library of Science (PLoS)
Subjects
Accountability
Adults
Algorithms
Artificial intelligence
Bias
Big Data
Biology and Life Sciences
Collaboration
Computer and Information Sciences
Demographics
End users
Engineering and Technology
Epidemiology
Ethics
General Data Protection Regulation
Health aspects
Health care industry
Health care reform
Health insurance
Health Insurance Portability & Accountability Act 1996-US
Health sciences
Internet of Things
Learning algorithms
Liability
Machine learning
Market entry
Medical personnel
Medical students
Medical treatment
Medicine
Medicine and Health Sciences
Mental disorders
Minority & ethnic groups
Nurses
People and Places
Personal information
Physical Sciences
Privacy
Provenance
Research and Analysis Methods
Safety and security measures
Schizophrenia
Services
Software
Technology application
Transparency
United Kingdom > UK
United States > US
Switzerland
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Summary:Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.
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I have read the journal’s policy and the authors of this manuscript have the following competing interests: EV has received speaking fees from SwissRe, Novartis R&D Academy, and Google Netherlands. IGC served as a consultant for Otsuka Pharmaceuticals advising on the use of digital medicine for its Abilify MyCite product. IGC is supported by the Collaborative Research Program for Biomedical Innovation Law, which is a scientifically independent collaborative research program supported by Novo Nordisk Foundation. AB served as a consultant for Celgene Corporation for the preparation of a workshop on pharmaceutical innovation and received honoraria from SwissRe for participating at an internal event on genome editing.
ISSN:1549-1676
1549-1277
1549-1676
DOI:10.1371/journal.pmed.1002689