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Breast cancer remains one of the leading causes of cancer-related deaths among women worldwide. Its impact on patients' lives and their loved ones is immense, underscoring the crucial need for more effective methods of early detection and diagnosis. This research proposes a CNN-based pipeline for classification of breast histology images. Over the past decades, artificial intelligence (AI) has emerged as a revolutionary technology in the field of medicine, offering new prospects to enhance the accuracy, speed, and accessibility of breast cancer diagnostics. It is within this context that our paper was developed, aiming to provide healthcare professionals with an efficient and reliable solution for cancer detection and classification using deep Learning. The proposed CNN model achieved an accuracy of 95.6% and an AUC of 0.98.

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Deep Learning Based Methods for Breast Cancer Diagnosis

  • 会议论文

  • 发表日期：

    2026年

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  • Sameh Souli,
  • Amira Soltani,
  • Rimah Amami,
  • Sadok Ben Yahia

摘要

Breast cancer remains one of the leading causes of cancer-related deaths among women worldwide. Its impact on patients' lives and their loved ones is immense, underscoring the crucial need for more effective methods of early detection and diagnosis. This research proposes a CNN-based pipeline for classification of breast histology images. Over the past decades, artificial intelligence (AI) has emerged as a revolutionary technology in the field of medicine, offering new prospects to enhance the accuracy, speed, and accessibility of breast cancer diagnostics. It is within this context that our paper was developed, aiming to provide healthcare professionals with an efficient and reliable solution for cancer detection and classification using deep Learning. The proposed CNN model achieved an accuracy of 95.6% and an AUC of 0.98.