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. 2018 Nov 6;15(11):e1002689.
doi: 10.1371/journal.pmed.1002689. eCollection 2018 Nov.

Machine learning in medicine: Addressing ethical challenges

Effy Vayena  1 , Alessandro Blasimme  1 , I Glenn Cohen  2
Affiliations

Machine learning in medicine: Addressing ethical challenges

Effy Vayena et al. PLoS Med. .

Abstract

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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Conflict of interest statement

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.

Figures

Fig 1
Fig 1. Imagine a medical software company developing a machine learning–based device.
The device performs fully automated analysis of histopathology slides from cancer patients and predicts genetic mutations in tumors solely based on these images. This inferred genetic information can be used either for prognostic purposes or to detect an indication for a targeted therapy. Users will not know which features of the images the algorithm associates with mutated genes or the biological explanation for these associations. The selling propositions of the device are that it can infer valuable genetic information early in the diagnostic process and be used in contexts in which genetic testing is not available by analyzing images shared by pathologists on a cloud-based platform. MLm, machine learning in medicine.
See this image and copyright information in PMC

References

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