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Exploiting graph kernels for high performance biomedical relation extraction
2018
Journal of Biomedical Semantics
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Among the graph kernels, we showed the ASM kernel as effective for biomedical relation extraction, with comparable performance to the APG kernel for datasets such as the CID-sentence level relation extraction ...
In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. ...
The Java based KeLP [22] framework was used for custom graph kernel implementation and can be downloaded from https://github.com/SAG-KeLP. ...
doi:10.1186/s13326-017-0168-3
pmid:29382397
pmcid:PMC5791373
fatcat:jn2u6rclizcxtcaoirt2podyky
A Single Kernel-Based Approach to Extract Drug-Drug Interactions from Biomedical Literature
2012
PLoS ONE
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In this paper, we propose a single kernel-based approach to extract DDIs from biomedical literature. ...
Experimental evaluations showed that our single kernel-based approach can achieve state-of-the-art performance on the publicly available DDI corpus without exploiting ...
We proposed the HSP kernel approach for DDIs extraction tasks and evaluated our approach on a publicly available DDI corpus. 2. ...
doi:10.1371/journal.pone.0048901
pmid:23133662
pmcid:PMC3486804
fatcat:aolryl7vvnc33onnm6566pmrm4
Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature
2016
BioMed Research International
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In this paper, we present a method of constructing two models for extracting the relations between the disease and symptom and symptom and therapeutic substance from biomedical texts, respectively. ...
that is, Co-Training and Tri-Training, are applied to utilize the unlabeled data to boost the relation extraction performance. ...
Introduction In recent years, with the rapid growth of biomedical literature, the technology of information extraction (IE) has been extensively applied to relation extraction in this literature, for example ...
doi:10.1155/2016/3594937
pmid:27822473
pmcid:PMC5086401
fatcat:es7x7kqvbrafrdmartruixiq4y
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances
[article]
2016
arXiv
pre-print
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Biomedical information extraction (BioIE) is important to many applications, including clinical decision support, integrative biology, and pharmacovigilance, and therefore it has been an active research ...
In addition, we dive into open information extraction and deep learning, two emerging and influential techniques and envision next generation of BioIE. ...
[62] conducted an analytical study on the performance of 13 types of kernels for PPI extraction, which suggests that the system performance benefits more from novel features than from novel kernel functions ...
arXiv:1606.07993v1
fatcat:7d5om7zxxzhoviiriasrfwg3xi
A logic-based relational learning approach to relation extraction: The OntoILPER system
2019
Engineering applications of artificial intelligence
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2020 pre-print arXiv:2001.04192v1 fatcat:urp7ypbrqjh27nclkgbygsmzi4
The proposed relational approach seems to be more suitable for Relation Extraction than statistical ones for several reasons that we argue. ...
Relation Extraction (RE), the task of detecting and characterizing semantic relations between entities in text, has gained much importance in the last two decades, mainly in the biomedical domain. ...
Development (CNPq/Brazil) for financial support (Grant No. 140791/2010-8). ...
doi:10.1016/j.engappai.2018.11.001
fatcat:zbhchesxxfb5zgqsq3qexdwlkm
Biomedical text categorization with concept graph representations using a controlled vocabulary
2012
Proceedings of the 11th International Workshop on Data Mining in Bioinformatics - BIOKDD '12
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In our representation we identify high level concepts extracted from a database of controlled biomedical terms and build a rich graph structure that contains important concepts and relationships. ...
Recent work using graph representations for text categorization has shown promising performance over conventional bag-of-words representation of text documents. ...
In addition, partial support for this research was provided by the National Science Foundation under grants DUE-0434581 and DUE-0434998, by the Institute for Museum and Library Services under grant LG- ...
doi:10.1145/2350176.2350181
dblp:conf/kdd/MishraHBS12
fatcat:lxpibzi5yngdzk3h6qqkqt7dky
A Labeled Graph Kernel for Relationship Extraction
[article]
2013
arXiv
pre-print
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In this paper, we propose an approach for Relationship Extraction (RE) based on labeled graph kernels. ...
The kernel we propose is a particularization of a random walk kernel that exploits two properties previously studied in the RE literature: (i) the words between the candidate entities or connecting them ...
[19] performed a study to analyze how a very comprehensive set of kernels for relationship extraction performs when dealing the task of extracting protein-protein interactions. ...
arXiv:1302.4874v1
fatcat:dlbkk6hvzjantlosvzii4pspyu
Drug–drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths
2017
Bioinformatics
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The ability to automatically extract DDIs described in the biomedical literature could further efforts for ongoing pharmacovigilance. ...
Effectively exploiting such information may improve DDI extraction. ...
Gevaert for helpful support and valuable discussions. We also gratefully acknowledge I. Segura-Bedmar, P. Martínez, M. Herrero-Zazo, T. Declerck for support of DDI 2013 corpus. ...
doi:10.1093/bioinformatics/btx659
pmid:29077847
pmcid:PMC6030919
fatcat:uxppknkndfbm5dyeupqtnpv7ua
BioPPISVMExtractor: A protein–protein interaction extractor for biomedical literature using SVM and rich feature sets
2010
Journal of Biomedical Informatics
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However, the amount of biomedical literature regarding protein interactions is increasing rapidly and it is difficult for interaction database curators to detect and curate protein interaction information ...
In addition, the Link Grammar extraction result feature is introduced to improve the precision rate. ...
David Corney for sharing the evaluation datasets and results. ...
doi:10.1016/j.jbi.2009.08.013
pmid:19706337
fatcat:rwb6ukl535dozaxtp3asbfrjna
Relation Extraction from Biomedical and Clinical Text: Unified Multitask Learning Framework
[article]
2020
arXiv
pre-print
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In the biomedical domain, extraction of regulatory pathways, metabolic processes, adverse drug reaction or disease models necessitates knowledge from the individual relations, for example, physical or ...
In this paper, we study the relation extraction task from three major biomedical and clinical tasks, namely drug-drug interaction, protein-protein interaction, and medical concept relation extraction. ...
They exploited kernel based method that uses the shallow linguistic and dependency kernel for extracting the relations. ...
arXiv:2009.09509v1
fatcat:fd3zpfjrybhrdpqkwgvpzrmisi
Leveraging syntactic and semantic graph kernels to extract pharmacokinetic drug drug interactions from biomedical literature
2016
BMC Systems Biology
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Conclusions: We presented a graph kernel based approach to combine syntactic and semantic information for extracting pharmacokinetic DDIs from Biomedical Literature. ...
Experimental results showed that our proposed approach could extract PK DDIs from literature effectively, which significantly enhanced the performance of the original all-path graph kernel based on dependency ...
Conclusions In this study, two types of semantic information, shallow semantic representation and fine-grained semantic classes, were exploited for PK DDI extraction from biomedical text. ...
doi:10.1186/s12918-016-0311-2
pmid:27585838
pmcid:PMC5009562
fatcat:pao3vjdberggjhu2rrqkb4n7i4
Biomedical Relation Extraction: From Binary to Complex
2014
Computational and Mathematical Methods in Medicine
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Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. ...
We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more ...
Acknowledgments The authors thank the anonymous reviewers for their insightful comments. This work was funded by the National Natural Science Foundation of China (61103077) ...
doi:10.1155/2014/298473
pmid:25214883
pmcid:PMC4156999
fatcat:2vxivwh3zjgmdioqyet7g4enfq
Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings
2018
Proceedings of the BioNLP 2018 workshop
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We investigate the incorporation of character-based word representations into a standard CNN-based relation extraction model. ...
The AI2 system at SemEval-2017 Task 10 (ScienceIE): semisupervised end-to-end entity and relation extraction. In ...
Exploiting graph
kernels for high performance biomedical relation ex-
traction. Journal of Biomedical Semantics 9(1):7.
Nagesh C. Panyam, Karin M. ...
doi:10.18653/v1/w18-2314
dblp:conf/bionlp/NguyenV18
fatcat:c5kr2qb2ujcehp2nsrc2es3szu
Neighborhood hash graph kernel for protein–protein interaction extraction
2011
Journal of Biomedical Informatics
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In this paper, we propose an approach based on neighborhood hash graph kernel for this task. ...
In contrast to the existing graph kernel-based approaches for PPI extraction, the proposed approach not only has the capability to make use of full dependency graphs to represent the sentence structure ...
Computational complexity For completely computing the dependency graphs, existing PPI extraction systems based on graph kernel easily lead high computational complexity. ...
doi:10.1016/j.jbi.2011.08.011
pmid:21884822
fatcat:wn5ztbqptjhjlkfscy65pwtwha
Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings
[article]
2018
arXiv
pre-print
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We investigate the incorporation of character-based word representations into a standard CNN-based relation extraction model. ...
Through a task on the BioCreative-V CDR corpus, extracting relationships between chemicals and diseases, we show that models exploiting the character-based word representations improve on models that do ...
Exploiting graph kernels for high performance biomedical relation extraction. Journal of Biomedical Semantics 9(1):7. Nagesh C. Panyam, Karin M. ...
arXiv:1805.10586v1
fatcat:m5axhs7hrfhz5kmvhxz2vvljza
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