Superior skin cancer classification by the combination of human and artificial intelligence.

Journal: European journal of cancer (Oxford, England : 1990)
Published Date: Oct 1, 2019

Abstract

BACKGROUND: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. However, the combination of classifiers frequently yields superior results, both in machine learning and among humans. In this study, we investigated the potential benefit of combining human and artificial intelligence for skin cancer classification.

Authors

  • Achim Hekler
    National Center for Tumor Diseases, Department of Translational Oncology, German Cancer Research Center, Heidelberg, Germany.
  • Jochen S Utikal
    Department of Dermatology, Heidelberg University, Mannheim, Germany; Skin Cancer Unit, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Alexander H Enk
    Department of Dermatology, University Hospital Heidelberg, University of Heidelberg, Heidelberg, Germany.
  • Axel Hauschild
    Department of Dermatology, University Hospital Kiel, Kiel, Germany.
  • Michael Weichenthal
    Department of Dermatology, University Hospital Kiel, Kiel, Germany.
  • Roman C Maron
    National Center for Tumor Diseases, German Cancer Research Center, Heidelberg, Germany.
  • Carola Berking
    Department of Dermatology, University Hospital Munich, Ludwig Maximilian University of Munich, Munich, Germany.
  • Sebastian Haferkamp
    Department of Dermatology, University Hospital Regensburg, Regensburg, Germany.
  • Joachim Klode
    Department of Dermatology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany.
  • Dirk Schadendorf
    Department of Dermatology, University Hospital Essen, 45147 Essen, Germany.
  • Bastian Schilling
    Department of Dermatology, University Hospital Wuerzburg, Wuerzburg, Germany.
  • Tim Holland-Letz
    Department of Biostatistics, German Cancer Research Center, Heidelberg, Germany.
  • Benjamin Izar
    Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Christof von Kalle
    National Center for Tumor Diseases, Department of Translational Oncology, German Cancer Research Center, Heidelberg, Germany.
  • Stefan Fröhling
    National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany.
  • Titus J Brinker
    National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany.

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