Weakly supervised learning in thymoma histopathology classification: an interpretable approach.

Journal: Frontiers in medicine
Published Date: Dec 11, 2024

Abstract

INTRODUCTION: Thymoma classification is challenging due to its diverse morphology. Accurate classification is crucial for diagnosis, but current methods often struggle with complex tumor subtypes. This study presents an AI-assisted diagnostic model that combines weakly supervised learning with a divide-and-conquer multi-instance learning (MIL) approach to improve classification accuracy and interpretability.

Authors

  • Chunbao Wang
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Xianglong Du
    School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.
  • Xiaoyu Yan
    School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.
  • Xiali Teng
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Xiaolin Wang
    Department of Urology, Nantong Tumor Hospital, Nantong, Jiangsu, China.
  • Zhe Yang
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Hongyun Chang
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Yangyang Fan
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Caihong Ran
    Department of Pathology, Ngari Prefecture People's Hospital, Ngari, Tibet, China.
  • Jie Lian
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Chen Li
    School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Hansheng Li
    School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.
  • Lei Cui
    School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.
  • Yina Jiang
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals