Conditional random fields for clinical named entity recognition: A comparative study using Korean clinical texts.

Journal: Computers in biology and medicine
Published Date: Aug 1, 2018

Abstract

BACKGROUND: This study demonstrates clinical named entity recognition (NER) methods on the clinical texts of rheumatism patients in South Korea. Despite the recent increase in the adoption rate of the electronic health record (EHR) system in global health institutions, health information technologies for handling and acquisition of information from numerous unstructured texts in the EHR system are still in their developing stages. The aim of this study is to verify the conventional named entity recognition (NER) methods, namely dictionary-lookup-based string matching and conditional random fields (CRFs).

Authors

  • Wangjin Lee
    Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. Electronic address: jinsamdol@snu.ac.kr.
  • Kyungmo Kim
    Interdisciplinary program for Bioengineering, Seoul National University, Seoul 03080, South Korea.
  • Eun Young Lee
    Division of Rheumatology, Department of Internal Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. Electronic address: elee@snu.ac.kr.
  • Jinwook Choi
    Dept. of Biomedical Engineering, College of Medicine, Seoul National University 103, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. Electronic address: jinchoi@snu.ac.kr.

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