Ecological preferences and patient autonomy.

Healthcare systems contribute considerably to worldwide carbon emissions and therefore reinforce the negative health impacts of climate change. Significant attempts to reduce emissions have been made on the macro level of politics and on the institutional level. Less attention has been paid so far to decisions that take place at the micro level of immediate doctor-patient contact.

Clinicians' roles and necessary levels of understanding in the use of artificial intelligence: A qualitative interview study with German medical students.

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.

Impacts of Clinical Decision Support Systems on the Relationship, Communication, and Shared Decision-Making Between Health Care Professionals and Patients: Multistakeholder Interview Study.

Background: Clinical decision support systems (CDSSs) are increasingly being introduced into various domains of health care. Little is known so far about the impact of such systems on the health care professional-patient relationship, and there is a lack of agreement about whether and how patients should be informed about the use of CDSSs.

Objective: This study aims to explore, in an empirically informed manner, the potential implications for the health care professional-patient relationship and to underline the importance of this relationship when using CDSSs for both patients and future professionals.

Artificial Intelligence to support ethical decision-making for incapacitated patients: a survey among German anesthesiologists and internists.

Background: Artificial intelligence (AI) has revolutionized various healthcare domains, where AI algorithms sometimes even outperform human specialists. However, the field of clinical ethics has remained largely untouched by AI advances. This study explores the attitudes of anesthesiologists and internists towards the use of AI-driven preference prediction tools to support ethical decision-making for incapacitated patients.