Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.

Journal: JAMA network open
PMID: 30848813

Abstract

IMPORTANCE: Proper evaluation of the performance of artificial intelligence techniques in the analysis of digitized medical images is paramount for the adoption of such techniques by the medical community and regulatory agencies.

Authors

  • Guy Nir
    Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada.
  • Davood Karimi
    Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
  • S Larry Goldenberg
    University of British Columbia, Vancouver, BC, Canada.
  • Ladan Fazli
    Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada.
  • Brian F Skinnider
    Department of Pathology and Laboratory Medicine, Vancouver General Hospital, Vancouver, British Columbia, Canada.
  • Peyman Tavassoli
    Institute for Precision Medicine.
  • Dmitry Turbin
    Department of Pathology and Laboratory Medicine, Vancouver General Hospital, Vancouver, British Columbia, Canada.
  • Carlos F Villamil
    British Columbia Cancer Agency, Vancouver, British Columbia, Canada.
  • Gang Wang
    National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
  • Darby J S Thompson
    Emmes Canada, Burnaby, British Columbia, Canada.
  • Peter C Black
    Department of Urologic Sciences, University of British Columbia, Vancouver, BC.
  • Septimiu E Salcudean
    Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.

Keywords

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