CDRnN: A high performance chemical-disease recognizer in biomedical literature

Hsin Chun Lee, Hung Yu Kao

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Diseases/Chemical play central roles in many areas of biomedical research and healthcare. Consequently, aggregating the disease knowledge and treatment research reports becomes an extremely critical issue, especially in rapid-growth knowledge bases (e.g., PubMed). Thus, a framework of disease/chemical named entity recognition and normalization has become increasingly important for biomedical text mining. In this work, we not only define five diversities of disease names but also develop a system for disease/chemical mention recognition and normalization in biomedical texts. Our system utilizes an order 2 conditional random fields (CRFs) model to develop a recognition system and optimize the results by customizing several post-processing, including abbreviation resolution, consistency improvement, stopwords filtering, and adjectives reorganization. After evaluation, we obtained the best performance (86.9% of F-score) on disease normalization and (89.95% of Precision) on chemical normalization. These results suggest that our system is a high-performance and state of the art recognition system for disease/chemical recognition and normalization from biomedical literature.

原文English
主出版物標題Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
編輯Illhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
發行者Institute of Electrical and Electronics Engineers Inc.
頁面374-379
頁數6
ISBN(電子)9781509030491
DOIs
出版狀態Published - 2017 十二月 15
事件2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
持續時間: 2017 十一月 132017 十一月 16

出版系列

名字Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
國家United States
城市Kansas City
期間17-11-1317-11-16

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics

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