Florian Funer

• MD MA Mag theol
• PostDoc Position at University of Tübingen

Background Patients are confronted with the digital transformation of medicine, yet there is a paucity of studies that discuss the patient perspective on AI-based clinical decision support systems (AI-CDSS). Our study addresses this research gap by focusing on their needs and concerns, especially regarding trust, responsibility, and self-determinat...

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...

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. Objecti...

Bioethics has developed approaches to address ethical issues in health care, similar to how technology ethics provides guidelines for ethical research on artificial intelligence, big data, and robotic applications. As these digital technologies are increasingly used in medicine, health care and public health, thus, it is plausible that the approach...

Zusammenfassung Klinische Entscheidungsunterstützungssysteme ( Clinical Decision Support Systems [CDSS]), die auf künstlicher Intelligenz (KI) basieren, kommen als komplexe soziotechnische Innovationen zunehmend in Medizin und Pflege zum Einsatz, um die Qualität und Effizienz der Versorgung insgesamt zu verbessern und gleichzeitig begrenzten finanz...

The research and regulatory levels for data-intensive research in medicine are divergent. This results in a heterogeneous global field of regulating institutions with regionally unequal regulations, both in terms of the depth and restrictiveness of regulations. Despite or precisely because of the lack of globally binding regulation, nonbinding or o...

The introduction of AI support tools raises questions about the normative orientation of medical practice and the need to rethink its basic concepts. One of these concepts that is central to the discussion is the physician’s autonomy and its appropriateness in the face of high-powered AI applications. In this essay, a differentiation of the physici...

Inequities shape the everyday experiences and life chances of individuals at the margins of societies and are often associated with lower health and particular challenges in accessing quality treatment and support. This fact is even more dramatic for those individuals who live at the nexus of different marginalized groups and thus may face multiple...

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...

Der Einsatz von Systemen zur klinischen Entscheidungsunterstützung eröffnet der Medizin und dem Gesundheitsbereich vielversprechende Möglichkeiten. Vor allem nicht-regelbasierte Algorithmen wecken zunehmend das Interesse unterschiedlicher Fachdisziplinen, um Erkenntnisse aus großen Datenmengen für (individualisierte) klinische Entscheidungen nutzba...

Häufig liegt in der zeitgenössischen Handlungstheorie der Fokus auf den mentalen Zuständen und Prozessen der Handlungssubjekte. Ansätze einer embodied agency verstehen dementgegen menschliches Handeln als immer schon körperlich und entwickeln davon ausgehend ihr Handlungsverständnis: Handeln wird durch den Körper ermöglicht, aber auch durch die ‚kö...

Developments in Machine Learning (ML) have attracted attention in a wide range of healthcare fields to improve medical practice and the benefit of patients. Particularly, this should be achieved by providing more or less automated decision recommendations to the treating physician. However, some hopes placed in ML for healthcare seem to be disappoi...

The initial successes in recent years in harnessing machine learning (ML) technologies to improve medical practice and benefit patients have attracted attention in a wide range of healthcare fields. Particularly, it should be achieved by providing automated decision recommendations to the treating clinician. Some hopes placed in such ML-based syste...

Die Nutzung von Technologien wie Machine Learning (ML) birgt zahlreiche Potentiale zur Verbesserung der medizinischen Praxis und zur Behandlung von Patienten. Dies soll insbesondere durch die Bereitstellung mehr oder weniger automatisierter Entschei- dungsempfehlungen erreicht werden. Einige Hoffnungen in ML-basierte Systeme schei- nen jedoch im Fa...

Zusammenfassung Zunehmend gewinnen Health Apps an Bedeutung für eine präventive und eigenverantwortliche Ausrichtung des Gesundheitssystems. Die meisten dieser digitalen Gesundheitsanwendungen (DiGA) basieren derzeit auf sog. Selftracking-Technologien, mit deren Hilfe physiologische und psychische Daten sensorgestützt aufgezeichnet und diese zumeis...

Im Zuge der Reflexion über die Zuteilung intensivmedizinischer Therapieressour-cen im Kontext von COVID-19 wurde u. a. die Frage kontrovers diskutiert, ob die laufende Behandlung einer Person zugunsten eines prognostisch günstigeren Dritten abgebrochen werden dürfe, sofern die bestehenden Ressourcen eine Behandlung beider nicht zuließen (sog. Verla...

Background: Older adults have increased risks of balance issues and falls when walking and performing turns in daily situations. Changes of prioritization during different walking situations associated with dual tasking may contribute to these deficits. The objective of this study was therefore to investigate whether older adults demonstrate change...