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Breast cancer, the most common cancer in women, relies on biomarkers for diagnostic and prognostic tasks, including tumor subtyping and treatment planning. SOX2, a transcription factor associated with therapeutic resistance, shows promise as a prognostic biomarker. This paper presents a deep learning algorithm for the classification of SOX2 expression levels in whole slide images of breast cancer. By automating the classification of SOX2 expression, the proposed algorithm addresses the need for efficient and objective biomarker assessment.

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Deep Learning-Based Classification of SOX2 Expression in Breast Cancer

  • 会议论文

  • 发表日期：

    2025年

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  • Laura Valeria Perez-Herrera,
  • María Jesús García-González,
  • Maria dM Vivanco,
  • Iván Macía Oliver,
  • Karen Lopez-Linares

摘要

Breast cancer, the most common cancer in women, relies on biomarkers for diagnostic and prognostic tasks, including tumor subtyping and treatment planning. SOX2, a transcription factor associated with therapeutic resistance, shows promise as a prognostic biomarker. This paper presents a deep learning algorithm for the classification of SOX2 expression levels in whole slide images of breast cancer. By automating the classification of SOX2 expression, the proposed algorithm addresses the need for efficient and objective biomarker assessment.