Prospective Analysis Using a Novel CNN Algorithm to Distinguish Atypical Ductal Hyperplasia From Ductal Carcinoma in Situ in Breast.

Journal: Clinical breast cancer
PMID: 32680766

Abstract

INTRODUCTION: We previously developed a convolutional neural networks (CNN)-based algorithm to distinguish atypical ductal hyperplasia (ADH) from ductal carcinoma in situ (DCIS) using a mammographic dataset. The purpose of this study is to further validate our CNN algorithm by prospectively analyzing an unseen new dataset to evaluate the diagnostic performance of our algorithm.

Authors

  • Simukayi Mutasa
    Department of Radiology, Columbia University Medical Center, New York, New York 10032.
  • Peter Chang
    Department of Urology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • John Nemer
    Department of Radiology, Columbia University Medical Center, 622 West 168th Street, PB-1-301, New York, NY, 10032, USA.
  • Eduardo Pascual Van Sant
    Department of Radiology, Columbia University Medical Center, New York, NY, USA.
  • Mary Sun
    Department of Radiology, Columbia University Medical Center, 622 West 168th Street, PB-1-301, New York, NY, 10032, USA.
  • Alison McIlvride
    Department of Radiology, Columbia University Medical Center, New York, NY.
  • Maham Siddique
    Department of Radiology, Columbia University Medical Center, New York, NY.
  • Richard Ha
    Department of Radiology, Columbia University Medical Center, New York, NY.

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