Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.

Journal: European journal of cancer (Oxford, England : 1990)
PMID: 33465706

Abstract

BACKGROUND: Studies systematically unravelling possible causes for false diagnoses of deep learning convolutional neural networks (CNNs) are scarce, yet needed before broader application.

Authors

  • Julia K Winkler
    Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Katharina Sies
    Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Christine Fink
  • Ferdinand Toberer
  • Alexander Enk
    Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Mohamed S Abassi
    Faculty of Computer Science and Mathematics, University of Passau, Passau, Germany.
  • Tobias Fuchs
    Department of Research and Development, FotoFinder Systems GmbH, Bad Birnbach, Germany.
  • Holger A Haenssle
    Department of Dermatology, University of Heidelberg, Heidelberg, Germany. Electronic address: holger.haenssle@med.uni-heidelberg.de.

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