Clinical prediction of pathological complete response in breast cancer: a machine learning study.

Journal: BMC cancer
Published Date: May 23, 2025

Abstract

BACKGROUND: This study aimed to develop and validate machine learning models to predict pathological complete response (pCR) after neoadjuvant therapy in patients with breast cancer patients.

Authors

  • Chongwu He
    Department of Breast Surgery, Jiangxi Cancer Hospital＆Institute，Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang 330029, Jiangxi Province, China (C.H., X.Z., T.Y.).
  • Tenghua Yu
    Department of Breast Surgery, Jiangxi Cancer Hospital＆Institute，Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang 330029, Jiangxi Province, China (C.H., X.Z., T.Y.). Electronic address: tengyeyu2024@163.com.
  • Liu Yang
    Department of Ultrasound, Hunan Children's Hospital, Changsha, China.
  • Longbo He
    Department of Breast Surgery, The Second Affiliated Hospital of Nanchang Medical College, Jiangxi Cancer Hospital, Nanchang, Jiangxi Province, China.
  • Jin Zhu
    Department of Laboratory, Quzhou People's Hospital, Quzhou, Zhejiang, China, qzhosp@163.com.
  • Jing Chen
    Department of Vascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China.

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