Extraction of drug-drug interaction using neural embedding

Wen Juan Hou*, Bamfa Ceesay


研究成果: 雜誌貢獻期刊論文同行評審

10 引文 斯高帕斯(Scopus)


Information on changes in a drug's effect when taken in combination with a second drug, known as drug-drug interaction (DDI), is relevant in the pharmaceutical industry. DDIs can delay, decrease, or enhance absorption of either drug and thus decrease or increase their action or cause adverse effects. Information Extraction (IE) can be of great benefit in allowing identification and extraction of relevant information on DDIs. We here propose an approach for the extraction of DDI from text using neural word embedding to train a machine learning system. Results show that our system is competitive against other systems for the task of extracting DDIs, and that significant improvements can be achieved by learning from word features and using a deep-learning approach. Our study demonstrates that machine learning techniques such as neural networks and deep learning methods can efficiently aid in IE from text. Our proposed approach is well suited to play a significant role in future research.

期刊Journal of Bioinformatics and Computational Biology
出版狀態已發佈 - 2018 12月 1

ASJC Scopus subject areas

  • 生物化學
  • 分子生物學
  • 電腦科學應用


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