Named entity recognition in Chinese medical records based on cascaded conditional random field

Yang Yan, Dun Wei Wen, Yun Ji Wang, Ke Wang

Research output: Contribution to journalJournal Articlepeer-review

12 Citations (Scopus)

Abstract

A new method for named entity recognition in Chinese medical records based on cascaded Conditional Random Fields (CRFs) is proposed. The first layer of the cascaded CRFs is used to identify the basic named entities of body parts and diseases. Then, the identified results are fed to the second layer for recognition of nested named entities for complex diseases and clinical symptoms. A new combination feature, composed of part-of-speech features and named entity features, is defined. This new feature together with the character features, word boundary features and context features in a sentence are taken as the feature set of the second layer. In the experiments based on CRF++, the proposed method yields a 3% higher F-score than cascaded CRF without the combination feature. Moreover, compared to single layer CRF method, it yields a 7% higher F-score, a significant increase in overall performance.

Original languageEnglish
Pages (from-to)1843-1848
Number of pages6
JournalJilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)
Volume44
Issue number6
DOIs
Publication statusPublished - 1 Nov. 2014

Keywords

  • Cascaded conditional random field
  • Chinese medical records
  • Conditional random field
  • Information processing
  • Named entity recognition

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