Deep Learning Predicts Molecular Subtype of Muscle-invasive Bladder Cancer from Conventional Histopathological Slides.

Journal: European urology
Published Date: Apr 27, 2020

Abstract

BACKGROUND: Muscle-invasive bladder cancer (MIBC) is the second most common genitourinary malignancy, and is associated with high morbidity and mortality. Recently, molecular subtypes of MIBC have been identified, which have important clinical implications.

Authors

  • Ann-Christin Woerl
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany; Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Markus Eckstein
    Institute of Pathology, University Hospitals Erlangen, Erlangen, Germany.
  • Josephine Geiger
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany; Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Daniel C Wagner
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
  • Tamas Daher
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
  • Philipp Stenzel
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
  • Aurélie Fernandez
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
  • Arndt Hartmann
    Institute of Pathology, University Hospital of Friedrich-Alexander-University Erlangen-Nürnberg, Germany.
  • Michael Wand
    Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Wilfried Roth
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany.
  • Sebastian Foersch
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany. Electronic address: sebastian.foersch@unimedizin-mainz.de.

Keywords

External Resources

Popular Topics
Recent Journals