Leukocyte deep learning classification assessment using Shapley additive explanations algorithm.

Journal: International journal of laboratory hematology
Published Date:

Abstract

INTRODUCTION: A peripheral blood smear is a basic test for hematological disease diagnosis. This test is performed manually in many places worldwide, which requires both time and qualified staff. Large laboratories are equipped with digital morphology analyzers, some of which are based on deep learning methods. However, it is difficult to explain to scientists how they work. In this paper, we proposed to add an explanatory factor to enhance the interpretability of deep learning models in leukocyte classification.

Authors

  • Adrian Michalski
    Department of Analytical Chemistry, Faculty of Pharmacy, University of Nicolaus Copernicus, Collegium Medicum, Bydgoszcz, Poland.
  • Konrad Duraj
    Department of Biosensors and Processing of Biomedical Signals, Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.
  • BogumiƂa Kupcewicz
    Department of Analytical Chemistry, Faculty of Pharmacy, University of Nicolaus Copernicus, Collegium Medicum, Bydgoszcz, Poland.