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Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists (2002.04500v1)

Published 11 Feb 2020 in eess.IV, cs.CV, and q-bio.QM

Abstract: While the Gleason score is the most important prognostic marker for prostate cancer patients, it suffers from significant observer variability. AI systems, based on deep learning, have proven to achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of fourteen observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard significantly increased (quadratically weighted Cohen's kappa, 0.799 vs 0.872; p=0.018). Our results show the added value of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.

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Authors (20)
  1. Wouter Bulten (7 papers)
  2. Maschenka Balkenhol (6 papers)
  3. Jean-Joël Awoumou Belinga (1 paper)
  4. Américo Brilhante (1 paper)
  5. Aslı Çakır (5 papers)
  6. Xavier Farré (1 paper)
  7. Katerina Geronatsiou (1 paper)
  8. Vincent Molinié (1 paper)
  9. Guilherme Pereira (1 paper)
  10. Paromita Roy (1 paper)
  11. Günter Saile (1 paper)
  12. Paulo Salles (1 paper)
  13. Ewout Schaafsma (1 paper)
  14. Joëlle Tschui (1 paper)
  15. Anne-Marie Vos (1 paper)
  16. Hester van Boven (2 papers)
  17. Robert Vink (2 papers)
  18. Jeroen van der Laak (23 papers)
  19. Christina Hulsbergen-van de Kaa (3 papers)
  20. Geert Litjens (33 papers)
Citations (120)