Evaluation of the predictive ability of ultrasound-based assessment of breast cancer using BI-RADS natural language reporting against commercial transcriptome-based tests.

Journal: PloS one
Published Date: Jan 10, 2020

Abstract

PURPOSE: The objective of this study was to assess the classification capability of Breast Imaging Reporting and Data System (BI-RADS) ultrasound feature descriptors targeting established commercial transcriptomic gene signatures that guide management of breast cancer.

Authors

  • Neema Jamshidii
    UCLA Department of Radiological Sciences, Los Angeles, CA, United States of America.
  • Jason Chang
    UCLA David Geffen School of Medicine, Los Angeles, CA, United States of America.
  • Kyle Mock
    Harbor-UCLA Medical Center, Department of Surgery, Los Angeles, CA, United States of America.
  • Brian Nguyen
    Harbor-UCLA Medical Center, Department of Surgery, Los Angeles, CA, United States of America.
  • Christine Dauphine
    Harbor-UCLA Medical Center, Department of Surgery, Los Angeles, CA, United States of America.
  • Michael D Kuo
    Department of Radiology, The University of Hong Kong, Hong Kong, China.

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