Deployment of a Machine Learning Algorithm in a Real-World Cohort for Quality Control Monitoring of Human Epidermal Growth Factor-2-Stained Clinical Specimens in Breast Cancer.

Journal: Archives of pathology & laboratory medicine
Published Date: Aug 1, 2025

Abstract

CONTEXT.—: Precise determination of biomarker status is necessary for clinical trial enrollment and endpoint analyses, as well as for optimal treatment determination in real-world practice. However, variabilities may be introduced into this process due to the processing of clinical specimens by different laboratories and assessment by distinct pathologists. Machine learning tools have the potential to minimize inconsistencies, although their use is not presently widespread.

Authors

  • Benjamin Glass
    PathAI, Boston, MA.
  • Michel E Vandenberghe
  • Surya Teja Chavali
    Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, India. Electronic address: chavali2@wisc.edu.
  • Syed Ashar Javed
    From PathAI, Boston, Massachusetts (Glass, Chavali, Javed, Resnick, Pokkalla, Elliott, Rao, Sridharan, Brosnan-Cashman, Wapinski, Montalto, Beck).
  • Murray Resnick
    PathAI, Boston, MA.
  • Harsha Pokkalla
    PathAI, Boston, MA.
  • Hunter Elliott
    PathAI, Boston, MA.
  • Sudha Rao
    Verily Life Sciences LLC, San Francisco, California.
  • Shamira Sridharan
    University of Illinois, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, Quantitative Light Imaging Laboratory, Urbana-Champaign, Illinois, United States.
  • Jacqueline A Brosnan-Cashman
    From PathAI, Boston, Massachusetts (Glass, Chavali, Javed, Resnick, Pokkalla, Elliott, Rao, Sridharan, Brosnan-Cashman, Wapinski, Montalto, Beck).
  • Ilan Wapinski
    PathAI, Boston, MA.
  • Michael Montalto
    PathAI, Boston, MA, USA.
  • Andrew H Beck
  • Craig Barker
    Personalised Healthcare &Biomarkers, IMED Biotech Unit, AstraZeneca, HODGKIN, C/o B310 Cambridge Science Park, Milton Road, Cambridge, CB4 0WG, United Kingdom.

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