Role of artificial intelligence in haematolymphoid diagnostics.

Journal: Histopathology
PMID:

Abstract

The advent of digital pathology and the deployment of high-throughput molecular techniques are generating an unprecedented mass of data. Thanks to advances in computational sciences, artificial intelligence (AI) approaches represent a promising avenue for extracting relevant information from complex data structures. From diagnostic assistance to powerful research tools, the potential fields of application of machine learning techniques in pathology are vast and constitute the subject of considerable research work. The aim of this article is to provide an overview of the potential applications of AI in the field of haematopathology and to define the role that these emerging technologies could play in our laboratories in the short to medium term.

Authors

  • Charlotte Syrykh
    Institut Universitaire du Cancer-Oncopole, Pathology Department, F-31059 Toulouse, France.
  • Michiel van den Brand
    Department of Pathology, Radboud University Medical Center, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
  • Jakob Nikolas Kather
    Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
  • Camille Laurent
    Department of Pathology, IUCT Oncopole, Toulouse, France; INSERM, U1037, Research Center In Cancer of Toulouse, laboratoire d'excellence TOUCAN, Toulouse, France. Electronic address: laurent.camille@iuct-oncopole.fr.