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.
View Article and Find Full Text PDFBackground: 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.
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.
View Article and Find Full Text PDFActa Orthop Scand
February 2000
The pathogenesis of Achilles tendon rupture remains unclear, but vascular patterns may play an important role. We determined the intravascular volume of the Achilles tendon using a new method with injection of radioisotopes. A solution of Tc-99m and gelatin-ink was injected into the lower limbs of body donors.
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