External Validation of a Commercial Artificial Intelligence Algorithm on a Diverse Population for Detection of False Negative Breast Cancers.

Journal: Journal of breast imaging
Published Date: Jan 25, 2025

Abstract

OBJECTIVE: There are limited data on the application of artificial intelligence (AI) on nonenriched, real-world screening mammograms. This work aims to evaluate the ability of AI to detect false negative cancers not detected at the time of screening when reviewed by the radiologist alone.

Authors

  • S Reed Plimpton
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Hannah Milch
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Christopher Sears
    Ananomouse Corporation, Newton, MA 02459, United States.
  • James Chalfant
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Anne Hoyt
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Cheryce Fischer
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • William Hsu
    Medical & Imaging Informatics, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA 90024, USA.
  • Melissa Joines
    Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

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