Closing the loop for AI-ready radiology.

Journal: RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Published Date: Aug 15, 2023

Abstract

BACKGROUND: In recent years, AI has made significant advancements in medical diagnosis and prognosis. However, the incorporation of AI into clinical practice is still challenging and under-appreciated. We aim to demonstrate a possible vertical integration approach to close the loop for AI-ready radiology.

Authors

  • Moritz Fuchs
    Informatics, TU Darmstadt, Germany.
  • Camila Gonzalez
    Informatics, TU Darmstadt, Germany.
  • Yannik Frisch
    Informatics, TU Darmstadt, Germany.
  • Paul Hahn
    Informatics, TU Darmstadt, Germany.
  • Philipp Matthies
    AI, Smart Reporting GmbH, München, Germany.
  • Maximilian Gruening
    Interorganisational Informationssystems, Georg-August-Universität Göttingen, Goettingen, Germany.
  • Daniel Pinto Dos Santos
    Department of Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Thomas Dratsch
    Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany. t.dratsch@mac.comn.
  • Moon Kim
    USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, 10300 Baltimore Ave., Beltsville, MD 20705, USA.
  • Felix Nensa
    Institute for AI in Medicine (IKIM), University Hospital Essen, 45131 Essen, Germany.
  • Manuel Trenz
    Interorganisational Informationssystems, Georg-August-Universität Göttingen, Goettingen, Germany.
  • Anirban Mukhopadhyay
    Zuse Institute Berlin, Berlin, Germany.

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