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SemEval-2013 Task 9 : Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013)
Isabel Segura-Bedmar
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Paloma Martínez
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María Herrero-Zazo
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Paper Details:
Month: June
Year: 2013
Location: Atlanta, Georgia, USA
Venue:
*SEMEVAL |
Citations
URL
Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information
Masaki Asada
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Makoto Miwa
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Yutaka Sasaki
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Johannes Welbl
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Pontus Stenetorp
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Sebastian Riedel
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FBK-irst : A Multi-Phase Kernel Based Approach for Drug-Drug Interaction Detection and Classification that Exploits Linguistic Information
Md. Faisal Mahbub Chowdhury
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Alberto Lavelli
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WBI-NER: The impact of domain-specific features on the performance of identifying and classifying mentions of drugs
Tim Rocktäschel
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Torsten Huber
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Michael Weidlich
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Ulf Leser
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UEM-UC3M: An Ontology-based named entity recognition system for biomedical texts.
Daniel Sanchez-Cisneros
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Fernando Aparicio Gali
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WBI-DDI: Drug-Drug Interaction Extraction using Majority Voting
Philippe Thomas
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Mariana Neves
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Tim Rocktäschel
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Ulf Leser
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NIL_UCM: Extracting Drug-Drug interactions from text through combination of sequence and tree kernels
Behrouz Bokharaeian
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Alberto Díaz
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UTurku: Drug Named Entity Recognition and Drug-Drug Interaction Extraction Using SVM Classification and Domain Knowledge
Jari Björne
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Suwisa Kaewphan
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Tapio Salakoski
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UWM-TRIADS: Classifying Drug-Drug Interactions with Two-Stage SVM and Post-Processing
Majid Rastegar-Mojarad
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Richard D. Boyce
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Rashmi Prasad
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UColorado_SOM: Extraction of Drug-Drug Interactions from Biomedical Text using Knowledge-rich and Knowledge-poor Features
Negacy Hailu
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Lawrence E. Hunter
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K. Bretonnel Cohen
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TEES 2.1: Automated Annotation Scheme Learning in the BioNLP 2013 Shared Task
Jari Björne
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Tapio Salakoski
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Extracting Drug-Drug Interactions with Attention CNNs
Masaki Asada
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Makoto Miwa
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Yutaka Sasaki
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POMELO: Medline corpus with manually annotated food-drug interactions
Thierry Hamon
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Vincent Tabanou
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Fleur Mougin
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Natalia Grabar
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Frantz Thiessard
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Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing
Jari Björne
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Tapio Salakoski
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http://www.cs.york.ac.uk/semeval-2013/task9/
http://www.cs.york.ac.uk/semeval-2013/task9/
http://www.whocc.no/atc
http://www.ncbi.nlm.nih.gov/mesh
http://www.cs.york.ac.uk/semeval-2013/task9/
http://www.cs.york.ac.uk/semeval-2013/task9/
http://jbjorne.github.io/TEES/
Field Of Study
Task
Named Entity Recognition
Information Extraction
Biomedical
Language
Spanish
Dataset
Biomedical Texts
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