David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi
British Medical Journal 364:I886 (2019)
| Authors |
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| Abstract |
Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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| Keywords | Machine learning Algorithms Medicine |
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Citations of this work BETA
Artificial Intelligence and Patient-Centered Decision-Making.Jens Christian Bjerring & Jacob Busch - 2020 - Philosophy and Technology 34 (2):349-371.
What the Near Future of Artificial Intelligence Could Be.Luciano Floridi - 2019 - Philosophy and Technology 32 (1):1-15.
How to Design AI for Social Good: Seven Essential Factors.Luciano Floridi, Josh Cowls, Thomas C. King & Mariarosaria Taddeo - 2020 - Science and Engineering Ethics 26 (3):1771-1796.
The explanation game: a formal framework for interpretable machine learning.David S. Watson & Luciano Floridi - forthcoming - Synthese:1-32.
What’s in the Box?: Uncertain Accountability of Machine Learning Applications in Healthcare.Ma'N. Zawati & Michael Lang - 2020 - American Journal of Bioethics 20 (11):37-40.
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