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  1. Responsibility and decision-making authority in using clinical decision support systems: an empirical-ethical exploration of German prospective professionals’ preferences and concerns.Florian Funer, Wenke Liedtke, Sara Tinnemeyer, Andrea Diana Klausen, Diana Schneider, Helena U. Zacharias, Martin Langanke & Sabine Salloch - 2024 - Journal of Medical Ethics 50 (1):6-11.
    Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakeholders remain largely unexplored. Empirical research, however, may help to clarify the conceptual debate and its aspects in terms of their relevance for clinical practice. This study explores, from an ethical point of view, future healthcare professionals’ attitudes to potential changes of responsibility and decision-making (...)
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  • Medicine and machines.Henk ten Have & Bert Gordijn - 2022 - Medicine, Health Care and Philosophy 25 (2):165-166.
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  • When time is of the essence: ethical reconsideration of XAI in time-sensitive environments.Andreas Wabro, Markus Herrmann & Eva C. Winkler - forthcoming - Journal of Medical Ethics.
    The objective of explainable artificial intelligence systems designed for clinical decision support (XAI-CDSS) is to enhance physicians’ diagnostic performance, confidence and trust through the implementation of interpretable methods, thus providing for a superior epistemic positioning, a robust foundation for critical reflection and trustworthiness in times of heightened technological dependence. However, recent studies have revealed shortcomings in achieving these goals, questioning the widespread endorsement of XAI by medical professionals, ethicists and policy-makers alike. Based on a surgical use case, this article challenges (...)
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  • Clinicians’ roles and necessary levels of understanding in the use of artificial intelligence: A qualitative interview study with German medical students.F. Funer, S. Tinnemeyer, W. Liedtke & S. Salloch - 2024 - BMC Medical Ethics 25 (1):1-13.
    Background Artificial intelligence-driven Clinical Decision Support Systems (AI-CDSS) are being increasingly introduced into various domains of health care for diagnostic, prognostic, therapeutic and other purposes. A significant part of the discourse on ethically appropriate conditions relate to the levels of understanding and explicability needed for ensuring responsible clinical decision-making when using AI-CDSS. Empirical evidence on stakeholders’ viewpoints on these issues is scarce so far. The present study complements the empirical-ethical body of research by, on the one hand, investigating the requirements (...)
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  • The ethical requirement of explainability for AI-DSS in healthcare: a systematic review of reasons.Nils Freyer, Dominik Groß & Myriam Lipprandt - 2024 - BMC Medical Ethics 25 (1):1-11.
    Background Despite continuous performance improvements, especially in clinical contexts, a major challenge of Artificial Intelligence based Decision Support Systems (AI-DSS) remains their degree of epistemic opacity. The conditions of and the solutions for the justified use of the occasionally unexplainable technology in healthcare are an active field of research. In March 2024, the European Union agreed upon the Artificial Intelligence Act (AIA), requiring medical AI-DSS to be ad-hoc explainable or to use post-hoc explainability methods. The ethical debate does not seem (...)
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  • Clouds on the horizon: clinical decision support systems, the control problem, and physician-patient dialogue.Mahmut Alpertunga Kara - 2025 - Medicine, Health Care and Philosophy 28 (1):125-137.
    Artificial intelligence-based clinical decision support systems have a potential to improve clinical practice, but they may have a negative impact on the physician-patient dialogue, because of the control problem. Physician-patient dialogue depends on human qualities such as compassion, trust, and empathy, which are shared by both parties. These qualities are necessary for the parties to reach a shared understanding -the merging of horizons- about clinical decisions. The patient attends the clinical encounter not only with a malfunctioning body, but also with (...)
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