On assessing trustworthy AI in healthcare: Best practice for machine learning as a supportive tool to recognize cardiac arrest in emergency calls

Roberto V. Zicari, James Brusseau, Stig Nikolaj Blomberg, Helle Collatz Christensen, Megan Coffee, Marianna B. Ganapini, Sara Gerke, Thomas Krendl Gilbert, Eleanore Hickman, Elisabeth Hildt, Sune Holm, Ulrich Kühne, Vince I. Madai, Walter Osika, Andy Spezzatti, Eberhard Schnebel, Jesmin Jahan Tithi, Dennis Vetter, Magnus Westerlund, Renee WurthJulia Amann, Vegard Antun, Valentina Beretta, Frédérick Bruneault, Erik Campano, Boris Düdder, Alessio Gallucci, Emmanuel Goffi, Christoffer Bjerre Haase, Thilo Hagendorff, Pedro Kringen, Florian Möslein, Davi Ottenheimer, Matiss Ozols, Laura Palazzani, Martin Petrin, Karin Tafur, Jim Tørresen, Holger Volland, Georgios Kararigas

Research output: Contribution to journal › Journal article › Research › peer-review

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Laboratory for Trustworthy AI (External organisation)
Boris Düdder (Member)
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On assessing trustworthy AI in healthcare: Best practice for machine learning as a supportive tool to recognize cardiac arrest in emergency calls

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Laboratory for Trustworthy AI (External organisation)