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  1. Shared Decision‐Making and Maternity Care in the Deep Learning Age: Acknowledging and Overcoming Inherited Defeaters.Keith Begley, Cecily Begley & Valerie Smith - 2020 - Journal of Evaluation in Clinical Practice.
    In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds in (...)
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  • AI Support for Ethical Decision-Making Around Resuscitation: Proceed with Care.Nikola Biller-Andorno, Andrea Ferrario, Susanne Joebges, Tanja Krones, Federico Massini, Phyllis Barth, Georgios Arampatzis & Michael Krauthammer - forthcoming - Journal of Medical Ethics:medethics-2020-106786.
    Artificial intelligence systems are increasingly being used in healthcare, thanks to the high level of performance that these systems have proven to deliver. So far, clinical applications have focused on diagnosis and on prediction of outcomes. It is less clear in what way AI can or should support complex clinical decisions that crucially depend on patient preferences. In this paper, we focus on the ethical questions arising from the design, development and deployment of AI systems to support decision-making around cardiopulmonary (...)
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  • From Clinical Decision Support to Clinical Reasoning Support Systems.Sophie Baalen, Mieke Boon & Petra Verhoef - forthcoming - Journal of Evaluation in Clinical Practice.
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  • Limits of Trust in Medical AI.Joshua James Hatherley - 2020 - Journal of Medical Ethics 46 (7):478-481.
    Artificial intelligence is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI’s progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since AI systems (...)
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