A Comprehensive AI-Based Approach in Classifying Breast Lesions: Focusing on Improving Pathologists' Accuracy and Efficiency.

Journal: Clinical breast cancer
Published Date: Mar 26, 2025

Abstract

BACKGROUND: Accurate classification of breast lesions is essential for effective clinical decision-making and patient management. In this study, we evaluated an artificial intelligence (AI) solution to classify whole slide images (WSIs) of breast lesions.

Authors

  • Maryam Tahir
    Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH.
  • Yan Hu
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Himani Kumar
    Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH.
  • Nada Shaker
    Department of Pathology, University of California San Francisco, UCSF, San Francisco, CA.
  • David Kellough
    Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH.
  • Shaya Goodman
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Manuela Vecsler
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Giovanni Lujan
    Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH.
  • Wendy L Frankel
    Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH.
  • Anil V Parwani
    Department of Pathology, The Ohio State University Wexner Medical Centre, Columbus, OH, USA.
  • Zaibo Li
    Deparment of Pathology, The Ohio State Unversity, Columbus, Ohio, USA.

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