Detecting negation and scope in Chinese clinical notes using character and word embedding.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 23, 2016

Abstract

BACKGROUND AND OBJECTIVES: Researchers have developed effective methods to index free-text clinical notes into structured database, in which negation detection is a critical but challenging step. In Chinese clinical records, negation detection is particularly challenging because it may depend on upstream Chinese information processing components such as word segmentation [1]. Traditionally, negation detection was carried out mostly using rule-based methods, whose comprehensiveness and portability were usually limited. Our objectives in this paper are to: 1) Construct a large Chinese clinical notes corpus with negation annotated; 2) develop a negation detection tool for Chinese clinical notes; 3) evaluate the performance of character and word embedding features in Chinese clinical natural language processing.

Authors

  • Tian Kang
    Department of Biomedical Informatics, Columbia University, New York, USA.
  • Shaodian Zhang
    Biomedical Informatics, Columbia University, New York, NY, USA.
  • Nanfang Xu
    Department of Orthopaedics, Peking University Third Hospital, Beijing, China.
  • Dong Wen
    Center for Medical Informatics, Peking University, Beijing, China.
  • Xingting Zhang
    Center for Medical Informatics, Peking University, Beijing, China.
  • Jianbo Lei
    Clinical Research Center, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People's Republic of China.

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