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Accountability in the Machine Learning Pipeline: The Critical Role of Research Ethics Oversight
American Journal of Bioethics 20 (11):40-42 (2020)
Abstract
Char and colleagues provide a useful conceptual framework for the proactive identification of ethical issues arising throughout the lifecycle of machine learning applications in healthcare. Th...Author's Profile
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Citations of this work
A Framework to Evaluate Ethical Considerations with ML-HCA Applications—Valuable, Even Necessary, but Never Comprehensive.Danton Char, Michael Abràmoff & Chris Feudtner - 2020 - American Journal of Bioethics 20 (11):W6-W10.
References found in this work
Identifying Ethical Considerations for Machine Learning Healthcare Applications.Danton S. Char, Michael D. Abràmoff & Chris Feudtner - 2020 - American Journal of Bioethics 20 (11):7-17.
Clinical applications of machine learning algorithms: beyond the black box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
Special Report: The Ethics of Using QI Methods to Improve Health Care Quality and Safety.Mary Ann Baily, Melissa M. Bottrell, Joanne Lynn & Bruce Jennings - 2006 - Hastings Center Report 36 (4):S1-S40.
Do no harm: A roadmap for responsible machine learning for health care.J. Wiens, S. Saria, M. Sendak, M. Ghassemi, V. X. Liu & F. Doshi-Velez - 2019 - Nature Medicine 25.
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