Determining individual suitability for neoadjuvant systemic therapy in breast cancer patients through deep learning.

Journal: Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Published Date: Apr 28, 2024

Abstract

BACKGROUND: The survival advantage of neoadjuvant systemic therapy (NST) for breast cancer patients remains controversial, especially when considering the heterogeneous characteristics of individual patients.

Authors

  • Enzhao Zhu
    School of Medicine, Tongji University, Shanghai, China.
  • Linmei Zhang
    Department of Periodontics, Stomatological Hospital and Dental School of Tongji University, Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China.
  • Yixian Liu
    Department of Gynecology and Obstetrics, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China.
  • Tianyu Ji
    School of Medicine, Tongji University, Shanghai, China.
  • Jianmeng Dai
    School of Medicine, Tongji University, Shanghai, China.
  • Ruichen Tang
    College of Electronic and Information Engineering, Tongji University, Shanghai, China.
  • Jiayi Wang
    Department of Statistics, Texas A&M University.
  • Chunyu Hu
    College of Computer Science, Nankai University, Tianjin 300350, China.
  • Kai Chen
    Department of Critical Care Medicine, Fujian Provincial Key Laboratory of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian Provincial Center for Critical Care Medicine, Fuzhou, Fujian, China.
  • Qianyi Yu
    School of Medicine, Tongji University, Shanghai, China.
  • Qiuyi Lu
    School of Medicine, Tongji University, Shanghai, China.
  • Zisheng Ai
    Department of Medical Statistics, Tongji University School of Medicine, Shanghai 200092, China.

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