Using NLP in openEHR archetypes retrieval to promote interoperability: a feasibility study in China.

Journal: BMC medical informatics and decision making
Published Date: Jun 26, 2021

Abstract

BACKGROUND: With the development and application of medical information system, semantic interoperability is essential for accurate and advanced health-related computing and electronic health record (EHR) information sharing. The openEHR approach can improve semantic interoperability. One key improvement of openEHR is that it allows for the use of existing archetypes. The crucial problem is how to improve the precision and resolve ambiguity in the archetype retrieval.

Authors

  • Bo Sun
    College of Information Science and Technology, Beijing Normal University, Beijing, 100875, China. Electronic address: tosunbo@bnu.edu.cn.
  • Fei Zhang
    Key Laboratory of Smart City and Environmental Modeling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Ürümqi, 830046, People's Republic of China. zhangfei3s@163.com.
  • Jing Li
    Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
  • Yicheng Yang
    Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167 North Lishi Road, Xicheng District, Beijing, 100191, China.
  • Xiaolin Diao
    Department of Information Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167 North Lishi Road, Xicheng District, Beijing, 100037, China.
  • Wei Zhao
    Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, Jiangsu Province, P. R. China. lxy@jiangnan.edu.cn zhuye@jiangnan.edu.cn.
  • Ting Shu
    Department of Computer and Information Science, University of Macau, Taipa, Macau, mb35455@umac.mo.

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