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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Using natural language processing to extract health-related causality from Twitter messages ... Doan, Son; Yang, Elly W; Tilak, Sameer. - : arXiv, 2019 BASE Show details 2 Extracting health-related causality from twitter messages using natural language processing Doan, Son; Yang, Elly W.; Tilak, Sameer S.. - : BioMed Central, 2019 BASE Show details 3 A Preliminary Study of Clinical Concept Detection Using Syntactic Relations Torii, Manabu; Yang, Elly W.; Doan, Son. - : American Medical Informatics Association, 2018 BASE Show details 4 Rapid Adaptation of POS Tagging for Domain Specific Uses ... Miller, John E.; Bloodgood, Michael; Torii, Manabu. - : arXiv, 2014 BASE Show details 5 iSimp in BioC standard format: enhancing the interoperability of a sentence simplification system Peng, Yifan; Tudor, Catalina O.; Torii, Manabu; Wu, Cathy H.; Vijay-Shanker, K.. - : Oxford University Press, 2014 Abstract: This article reports the use of the BioC standard format in our sentence simplification system, iSimp, and demonstrates its general utility. iSimp is designed to simplify complex sentences commonly found in the biomedical text, and has been shown to improve existing text mining applications that rely on the analysis of sentence structures. By adopting the BioC format, we aim to make iSimp readily interoperable with other applications in the biomedical domain. To examine the utility of iSimp in BioC, we implemented a rule-based relation extraction system that uses iSimp as a preprocessing module and BioC for data exchange. Evaluation on the training corpus of BioNLP-ST 2011 GENIA Event Extraction (GE) task showed that iSimp sentence simplification improved the recall by 3.2% without reducing precision. The iSimp simplification-annotated corpora, both our previously used corpus and the GE corpus in the current study, have been converted into the BioC format and made publicly available at the project’s Web site: http://research.bioinformatics.udel.edu/isimp/. Keyword: Original Article URL: https://doi.org/10.1093/database/bau038 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028706 http://www.ncbi.nlm.nih.gov/pubmed/24850848 BASE Hide details 6 BioC: a minimalist approach to interoperability for biomedical text processing Comeau, Donald C.; Islamaj Doğan, Rezarta; Ciccarese, Paolo. - : Oxford University Press, 2013 BASE Show details 7 BioC: a minimalist approach to interoperability for biomedical text processing Comeau, Donald C.; Islamaj Doğan, Rezarta; Ciccarese, Paolo. - : Oxford University Press, 2013 BASE Show details 8 Rapid Adaptation of POS Tagging for Domain Specific Uses ... Miller, John; Bloodgood, Michael; Torii, Manabu. - : Digital Repository at the University of Maryland, 2006 BASE Show details 9 Rapid Adaptation of POS Tagging for Domain Specific Uses Miller, John; Bloodgood, Michael; Torii, Manabu. - : Association for Computational Linguistics, 2006 BASE Show details

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