Extraction of BI-RADS findings from breast ultrasound reports in Chinese using deep learning approaches.

Journal: International journal of medical informatics
Published Date: Aug 18, 2018

Abstract

BACKGROUND: The wide adoption of electronic health record systems (EHRs) in hospitals in China has made large amounts of data available for clinical research including breast cancer. Unfortunately, much of detailed clinical information is embedded in clinical narratives e.g., breast radiology reports. The American College of Radiology (ACR) has developed a Breast Imaging Reporting and Data System (BI-RADS) to standardize the clinical findings from breast radiology reports.

Authors

  • Shumei Miao
    Department of Information, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China; Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Tingyu Xu
    Department of Information, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China; Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Yonghui Wu
    Department of Health Outcomes and Biomedical Informatics.
  • Hui Xie
    Department of Breast Diseases, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China.
  • Jingqi Wang
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Shenqi Jing
    Department of Information, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China; Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Yaoyun Zhang
    Alibaba Damo Academy, 969 West Wen Yi Road, Yu Hang District, Hangzhou, Zhejiang, China.
  • Xiaoliang Zhang
    Department of Information, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China; Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Yinshuang Yang
    Department of Information, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China; Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Xin Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Tao Shan
    Department of Spine Surgery, The First People's Hospital of Hefei City, Hefei, Anhui, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Shui Wang
    Department of Breast Diseases, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China. Electronic address: ws0801@hotmail.com.
  • Yun Liu
    Google Health, Palo Alto, CA USA.

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