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Links to published journals:https://academic.oup.com/bioinformatics/article/32/22/3444/2525603

Indexed by:Journal Papers

Date of Publication:2016-11-15

Journal:Bioinformatics

Included Journals:SCI

Affiliation of Author(s):DaLian University of Technology

Place of Publication:J

Discipline:Engineering

First-Level Discipline:Biomedical Engineering

Volume:32

Issue:22

Page Number:3444-3453

Key Words:Deep learning, Drug-Drug Interaction Extraction, Convolutional Neural Network

Abstract:Motivation: Detecting drug-drug interaction (DDI) has become a vital part of public health safety. Therefore, using text mining techniques to extract DDIs from biomedical literature has received great attentions. However, this research is still at an early stage and its performance has much room to improve.
Results: In this article, we present a syntax convolutional neural network (SCNN) based DDI extraction method. In this method, a novel word embedding, syntax word embedding, is proposed to employ the syntactic information of a sentence. Then the position and part of speech features are intr