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  1. Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (7):4-20.
    Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...)
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  • 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.
    Along with potential benefits to healthcare delivery, machine learning healthcare applications raise a number of ethical concerns. Ethical evaluations of ML-HCAs will need to structure th...
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  • Ethics Consultation Quality Assessment Tool: A Novel Method for Assessing the Quality of Ethics Case Consultations Based on Written Records.Robert A. Pearlman, Mary Beth Foglia, Ellen Fox, Jennifer H. Cohen, Barbara L. Chanko & Kenneth A. Berkowitz - 2016 - American Journal of Bioethics 16 (3):3-14.
    Although ethics consultation is offered as a clinical service in most hospitals in the United States, few valid and practical tools are available to evaluate, ensure, and improve ethics consultation quality. The quality of ethics consultation is important because poor quality ethics consultation can result in ethically inappropriate outcomes for patients, other stakeholders, or the health care system. To promote accountability for the quality of ethics consultation, we developed the Ethics Consultation Quality Assessment Tool. ECQAT enables raters to assess the (...)
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