Machine learning-based fusion model for predicting HER2 expression in breast cancer by Sonazoid-enhanced ultrasound: a multicenter study.

Journal: Frontiers in medicine
Published Date:

Abstract

PURPOSE: To predict human epidermal growth factor receptor 2 (HER2) expression in breast cancer (BC) using Sonazoid-enhanced ultrasound in a machine learning-based model.

Authors

  • Huiting Zhang
    College of Data Science, Taiyuan University of Technology, Jinzhong 030600, China; Technology Research Centre of Spatial Information Network Engineering of Shanxi, Jinzhong 030600, China; Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province, Taiyuan, China, 030024.
  • Manlin Lang
    Department of Interventional Ultrasound, PLA Medical College & Chinese PLA General Hospital, Beijing, China.
  • Huiming Shen
    Department of Ultrasound, Southeast University Zhongda Hospital, Nanjing, 210009, Jiangsu Province, China.
  • Hang Li
    Beijing Academy of Quantum Information Sciences, Beijing 100193, China.
  • Ning Yang
    Department of Cardiology, Tianjin Chest Hospital, No 261, Taierzhuang South road, Jinnan district, Tianjin, 300222, China.
  • Bo Chen
  • Yixu Chen
    Department of Ultrasound, The Fifth People's Hospital of Chengdu, Chengdu, China.
  • Hong Ding
    Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. ding.hong@zs-hospital.sh.cn.
  • Weiping Yang
    Department of Ultrasound, Guangxi Medical University Cancer Hospital, Nanning, China.
  • Xiaohui Ji
    Department of Ultrasound, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
  • Ping Zhou
  • Ligang Cui
    Department of Ultrasound, Peking University Third Hospital, Beijing, China. Electronic address: cuiligang_bysy@126.com.
  • Jiandong Wang
    Department of Computer Science and Engineering,University of South Carolina, Columbia, 29208, SC, USA.
  • Wentong Xu
    General Surgery, Chinese PLA General Hospital, Beijing, China.
  • Xiuqin Ye
    Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China.
  • Zhixing Liu
    Department of Ultrasound Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Yu Yang
    Department of Obstetrics & Gynecology, the First Affiliated Hospital of Xi'an Jiaotong University, Xian, Shaanxi, China.
  • Tianci Wei
    Department of Ultrasound, The 2nd Affiliated Hospital of Harbin, Harbin, China.
  • Hui Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Yuanyuan Yan
    Department of Ultrasound, Zhengzhou Central Hospital, Zhengzhou, China.
  • Changjun Wu
    Ultrasound Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
  • Yiyun Wu
    Nanjing University of Chinese Medicine, Nanjing, 210029.
  • Jingwen Shi
    School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.
  • Yaxi Wang
  • Xiuxia Fang
    Department of Ultrasound, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.
  • Ran Li
    Department of Automation, Tsinghua University, Beijing, China.
  • Ping Liang
    Department of Pharmacy, The Fourth Hospital of Hebei Medical University Shijiazhuang 050000, Hebei, China.
  • Jie Yu
    Institute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, Ya'an, 625014, China.

Keywords

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