116 citations · 179 across the 11 of their papers we have counts for
5 papers · 1 filter
Advancing Trustworthy AI in Healthcare Through Meta-Research: Results of an Interdisciplinary Design-Thinking Workshop
Valerie Bürger, Marlie Besouw, Jana Fehr +26
Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields. To in…
Getting Ready for the EU AI Act in Healthcare. A call for Sustainable AI Development and Deployment
John Brandt Brodersen, Ilaria Amelia Caggiano, Pedro Kringen +6
Assessments of trustworthiness have become a cornerstone of responsible AI development. Especially in high-stakes fields like healthcare, aligning technical, evidence-based, and et…
Explainable AI: Definition and attributes of a good explanation for health AI
Evangelia Kyrimi, Scott McLachlan, Jared M Wohlgemut +4
Proposals of artificial intelligence (AI) solutions based on increasingly complex and accurate predictive models are becoming ubiquitous across many disciplines. As the complexity…
How to Assess Trustworthy AI in Practice
Roberto V. Zicari, Julia Amann, Frédérick Bruneault +17
This report is a methodological reflection on Z-Inspection. Z-Inspection is a holistic process used to evaluate the trustworthiness of A…
From Bit To Bedside: A Practical Framework For Artificial Intelligence Product Development In Healthcare
David Higgins, Vince I. Madai
Artificial Intelligence (AI) in healthcare holds great potential to expand access to high-quality medical care, whilst reducing overall systemic costs. Despite hitting the headline…