Mining patterns of drug-disease association from biomedical texts

Wen Juan Hou, Bo Syun Lee, Hung Chi Chen

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Drug repurposing aims to identify new indications for approved drugs, and it can promisingly reduce time and drug development costs. The goal of the paper, drug-disease relation extraction automatically from biomedical texts, is fundamental to the study of drug repurposing since lots of clinical case studies published in an unstructured textual form. To analyze the number of verbs and nouns pertinent to diseases and medications in the training data, two models with different drug-disease orders are established, and some rules are proposed at this phase. The first model is for the sentences with the order that the disease name precedes the drug name. The second model is for the reverse order to the first model. These verbs and nouns are then classified into categories of "pure association," "pure no association" and "neutrals." Among them, some neutrals are further verified by the Chi-square test method. As a result, the associations between diseases and medications are identified, which are called patterns later. Finally, the patterns are used in the test data to extract the disease and drug pairs. The best experimental results show the precision value of 100%, recall value of 89.0%, and F-score value of 94.2%.

原文英語
主出版物標題Proceedings of the 2018 8th International Conference on Bioscience, Biochemistry and Bioinformatics, ICBBB 2018
發行者Association for Computing Machinery
頁面84-90
頁數7
ISBN(電子)9781450353410
DOIs
出版狀態已發佈 - 2018 一月 18
事件8th International Conference on Bioscience, Biochemistry and Bioinformatics, ICBBB 2018 - Tokyo, 日本
持續時間: 2018 一月 182018 一月 20

出版系列

名字ACM International Conference Proceeding Series

其他

其他8th International Conference on Bioscience, Biochemistry and Bioinformatics, ICBBB 2018
國家/地區日本
城市Tokyo
期間2018/01/182018/01/20

ASJC Scopus subject areas

  • 軟體
  • 人機介面
  • 電腦視覺和模式識別
  • 電腦網路與通信

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