Improving Augmented Human Intelligence to Distinguish Burkitt Lymphoma From Diffuse Large B-Cell Lymphoma Cases.

Journal: American journal of clinical pathology
PMID: 32067039

Abstract

OBJECTIVES: To assess and improve the assistive role of a deep, densely connected convolutional neural network (CNN) to hematopathologists in differentiating histologic images of Burkitt lymphoma (BL) from diffuse large B-cell lymphoma (DLBCL).

Authors

  • Jeffrey S Mohlman
    Department of Pathology, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City.
  • Samuel D Leventhal
    Department of Computer Science, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City.
  • Taft Hansen
    Department of Pathology, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City.
  • Jessica Kohan
    Department of Pathology, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City.
  • Valerio Pascucci
    Department of Computer Science, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City.
  • Mohamed E Salama
    Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN, USA.

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