Artificial intelligence for triaging of breast cancer screening mammograms and workload reduction: A meta-analysis of a deep learning software.

Journal: Journal of medical screening
Published Date: Dec 20, 2023

Abstract

OBJECTIVE: Deep learning (DL) has shown promising results for improving mammographic breast cancer diagnosis. However, the impact of artificial intelligence (AI) on the breast cancer screening process has not yet been fully elucidated in terms of potential workload reduction. We aim to assess if AI-based triaging of breast cancer screening mammograms could reduce the radiologist's workload with non-inferior sensitivity.

Authors

  • Debora Xavier
    Federal University of Para, Belem, PA, Brazil.
  • Isabele Miyawaki
    Federal University of Parana, Curitiba, PR, Brazil.
  • Carlos Alberto Campello Jorge
    Federal University of Mato Grosso, Cuiaba, MT, Brazil.
  • Gabriela Batalini Freitas Silva
    Hospital Municipal Joao de Caires, Prado Ferreira, PR, Brazil.
  • Maxwell Lloyd
    Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Fabio Moraes
    Department of Oncology, Queen's University, Kingston, ON, Canada.
  • Bhavika Patel
    Department of Radiology, Mayo Clinic in Arizona, Scottsdale, AZ, 85259, USA.
  • Felipe Batalini
    Women's Cancer Program, Mayo Clinic Cancer Center, Phoenix, AZ, USA.

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