Development and validation of machine learning models for predicting HER2-zero and HER2-low breast cancers.

Journal: The British journal of radiology
PMID: 38991838

Abstract

OBJECTIVES: To develop and validate machine learning models for human epidermal growth factor receptor 2 (HER2)-zero and HER2-low using MRI features pre-neoadjuvant therapy (NAT).

Authors

  • Xu Huang
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Lei Wu
    Advanced Photonics Center, Southeast University, Nanjing, 210096, China.
  • Yu Liu
    Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Science, Beijing, China.
  • Zeyan Xu
    School of Medicine, South China University of Technology, Guangzhou 510006, China.
  • Chunling Liu
    Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
  • Zaiyi Liu
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Changhong Liang
    Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China.

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