Ontology boosted deep learning for disease name extraction from Twitter messages

[1]  Peter Nabende,et al.  Ontology driven machine learning approach for disease name extraction from Twitter messages , 2017, 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA).

[2]  Peter Nabende,et al.  An Ontology for Generalized Disease Incidence Detection on Twitter , 2017, HAIS.

[3]  Venkata Rama Kiran Garimella,et al.  Social Media Image Analysis for Public Health , 2015, CHI.

[4]  Janos X. Binder,et al.  DISEASES: Text mining and data integration of disease–gene associations , 2014, bioRxiv.

[5]  Quoc V. Le,et al.  Distributed Representations of Sentences and Documents , 2014, ICML.

[6]  Michael Blench,et al.  The Global Public Health Intelligence Network , 2013 .

[7]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[8]  Ernesto Diaz-Aviles,et al.  Tracking Twitter for epidemic intelligence: case study: EHEC/HUS outbreak in Germany, 2011 , 2012, WebSci '12.

[9]  Lars Juhl Jensen,et al.  DistiLD Database: diseases and traits in linkage disequilibrium blocks , 2011, Nucleic Acids Res..

[10]  Mizuki Morita,et al.  Twitter Catches The Flu: Detecting Influenza Epidemics using Twitter , 2011, EMNLP.

[11]  Aron Culotta,et al.  Towards detecting influenza epidemics by analyzing Twitter messages , 2010, SOMA '10.

[12]  Wolfgang Nejdl,et al.  How valuable is medical social media data? Content analysis of the medical web , 2009, Inf. Sci..

[13]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[14]  David M. Pennock,et al.  Using internet searches for influenza surveillance. , 2008, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[15]  Son Doan,et al.  BioCaster: detecting public health rumors with a Web-based text mining system , 2008, Bioinform..

[16]  S A Forbes,et al.  The Catalogue of Somatic Mutations in Cancer (COSMIC) , 2008, Current protocols in human genetics.

[17]  Kalina Bontcheva,et al.  GATE: an Architecture for Development of Robust HLT applications , 2002, ACL.

[18]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[19]  Qiang Chen,et al.  Identifying Diseases, Drugs, and Symptoms in Twitter , 2015, MedInfo.

[20]  J. Brownstein,et al.  Model Formulation: HealthMap: Global Infectious Disease Monitoring through Automated Classification and Visualization of Internet Media Reports , 2008, J. Am. Medical Informatics Assoc..

[21]  Beatrice Santorini,et al.  The Penn Treebank: An Overview , 2003 .