Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

This paper documents how an ethically aligned co-design methodology ensures trustworthiness in the early design phase of an artificial intelligence (AI) system component for healthcare. The system explains decisions made by deep learning networks analyzing images of skin lesions. The co-design of tr...

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Bibliographic Details
Main Authors: Roberto V. Zicari, Sheraz Ahmed, Julia Amann, Stephan Alexander Braun, John Brodersen, Frédérick Bruneault, James Brusseau, Erik Campano, Megan Coffee, Andreas Dengel, Boris Düdder, Alessio Gallucci, Thomas Krendl Gilbert, Philippe Gottfrois, Emmanuel Goffi, Christoffer Bjerre Haase, Thilo Hagendorff, Eleanore Hickman, Elisabeth Hildt, Sune Holm, Pedro Kringen, Ulrich Kühne, Adriano Lucieri, Vince I. Madai, Pedro A. Moreno-Sánchez, Oriana Medlicott, Matiss Ozols, Eberhard Schnebel, Andy Spezzatti, Jesmin Jahan Tithi, Steven Umbrello, Dennis Vetter, Holger Volland, Magnus Westerlund, Renee Wurth
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Human Dynamics
Subjects:
artificial intelligence
healthcare
trustworthy AI
ethics
malignant melanoma
Z-inspection®1
Online Access:https://www.frontiersin.org/articles/10.3389/fhumd.2021.688152/full

Internet

https://www.frontiersin.org/articles/10.3389/fhumd.2021.688152/full

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