Multichannel Convolutional Neural Network for Biological Relation Extraction
Joint Authors
Quan, Chanqin
Hua, Lei
Sun, Xiao
Bai, Wenjun
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The plethora of biomedical relations which are embedded in medical logs (records) demands researchers’ attention.
Previous theoretical and practical focuses were restricted on traditional machine learning techniques.
However, these methods are susceptible to the issues of “vocabulary gap” and data sparseness and the unattainable automation process in feature extraction.
To address aforementioned issues, in this work, we propose a multichannel convolutional neural network (MCCNN) for automated biomedical relation extraction.
The proposed model has the following two contributions: (1) it enables the fusion of multiple (e.g., five) versions in word embeddings; (2) the need for manual feature engineering can be obviated by automated feature learning with convolutional neural network (CNN).
We evaluated our model on two biomedical relation extraction tasks: drug-drug interaction (DDI) extraction and protein-protein interaction (PPI) extraction.
For DDI task, our system achieved an overall f-score of 70.2% compared to the standard linear SVM based system (e.g., 67.0%) on DDIExtraction 2013 challenge dataset.
And for PPI task, we evaluated our system on Aimed and BioInfer PPI corpus; our system exceeded the state-of-art ensemble SVM system by 2.7% and 5.6% on f-scores.
American Psychological Association (APA)
Quan, Chanqin& Hua, Lei& Sun, Xiao& Bai, Wenjun. 2016. Multichannel Convolutional Neural Network for Biological Relation Extraction. BioMed Research International،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1096984
Modern Language Association (MLA)
Quan, Chanqin…[et al.]. Multichannel Convolutional Neural Network for Biological Relation Extraction. BioMed Research International No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1096984
American Medical Association (AMA)
Quan, Chanqin& Hua, Lei& Sun, Xiao& Bai, Wenjun. Multichannel Convolutional Neural Network for Biological Relation Extraction. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1096984
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1096984