Adversarial attacks on medical machine learning

Emerging vulnerabilities demand new conversations With public and academic attention increasingly focused on the new role of machine learning in the health information economy, an unusual and no-longer-esoteric category of vulnerabilities in machine-learning systems could prove important. These vuln...

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Bibliographic Details
Published in:Science (American Association for the Advancement of Science) 2019-03, Vol.363 (6433), p.1287-1289
Main Authors: Finlayson, Samuel G., Bowers, John D., Ito, Joichi, Zittrain, Jonathan L., Beam, Andrew L., Kohane, Isaac S.
Format: Article
Language:English
Subjects:
Artificial intelligence
Fraud
Health care
Humans
Innovations
Insurance Claim Review
Learning algorithms
Machine Learning
Medical innovations
POLICY FORUM
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