Presenting machine learning model information to clinical end users with model facts labels

There is tremendous enthusiasm surrounding the potential for machine learning to improve medical prognosis and diagnosis. However, there are risks to translating a machine learning model into clinical care and clinical end users are often unaware of the potential harm to patients. This perspective p...

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Bibliographic Details
Main Authors: Mark P. Sendak, Michael Gao, Nathan Brajer, Suresh Balu
Format: article
Language:EN
Published: Nature Portfolio 2020
Subjects:
Online Access:https://doaj.org/article/04a32595eab3442b8044b66e5a84a0f7
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