Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights.

Journal: Neuropathology and applied neurobiology
Published Date:

Abstract

AIM: Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell typing. The current gold standard is based on microscopic examination by specialised technicians and neuropathologists, which is time-consuming, labour-intensive and subjective.

Authors

  • Leonille Schweizer
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Philipp Seegerer
    Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technical University of Berlin, 10623 Berlin, Germany.
  • Hee-Yeong Kim
  • René Saitenmacher
    Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.
  • Amos Muench
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Liane Barnick
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Anja Osterloh
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Carsten Dittmayer
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Ruben Jödicke
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Debora Pehl
    Department of Pathology, Vivantes Hospitals Berlin, Berlin, Germany.
  • Annekathrin Reinhardt
    Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
  • Klemens Ruprecht
    Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Department of Neurology, 10117 Berlin, Germany.
  • Werner Stenzel
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Annika K Wefers
    Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
  • Patrick N Harter
    Frankfurt Cancer Institute, Goethe University, Frankfurt am Main, Germany.
  • Ulrich Schüller
    Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Munich, Germany; Institute of Neuropathology, University Medical Center, Hamburg-Eppendorf, Germany; Research Institute Children's Cancer Center, Hamburg, Germany; Department of Pediatric Hematology and Oncology, University Medical Center, Hamburg-Eppendorf, Germany.
  • Frank L Heppner
    Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Maximilian Alber
    Berlin Big Data Center, Berlin Institute of Technology, Berlin, Germany.
  • Klaus-Robert Müller
    Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Deutschland.
  • Frederick Klauschen
    Pathologisches Institut, Ludwig-Maximilians-Universität München, Thalkirchner Str. 36, 80337, München, Deutschland. f.klauschen@lmu.de.