Turning user generated health-related content into actionable knowledge through text analytics services
暂无分享,去创建一个
Paloma Martínez | Isabel Segura-Bedmar | José L. Martínez | Julián Moreno Schneider | Adrián Luna | Ricardo Revert | Isabel Segura-Bedmar | J. Schneider | Paloma Martínez | José L. Martínez | Adrián Luna | Ricardo Revert
[1] M D Rawlins,et al. Pharmacovigilance: Paradise Lost, Regained or Postponed? , 1995, Journal of the Royal College of Physicians of London.
[2] Anthony R. Cox,et al. Patient reporting of adverse drug reactions , 2009 .
[3] Fan Yu,et al. Towards large-scale twitter mining for drug-related adverse events , 2012, SHB '12.
[4] Mark McClellan,et al. Drug safety reform at the FDA--pendulum swing or systematic improvement? , 2007, The New England journal of medicine.
[5] Graciela Gonzalez-Hernandez,et al. Utilizing social media data for pharmacovigilance: A review , 2015, J. Biomed. Informatics.
[6] Paloma Martínez,et al. Lessons learnt from the DDIExtraction-2013 Shared Task , 2014, J. Biomed. Informatics.
[7] Miriam C.J.M. Sturkenboom,et al. Adverse Drug Reaction-Related Hospitalisations , 2006, Drug safety.
[8] Paloma Martínez,et al. Pharmacovigilance through the development of text mining and natural language processing techniques , 2015, J. Biomed. Informatics.
[9] Henrik Druid,et al. Incidence of fatal adverse drug reactions: a population based study. , 2008, British journal of clinical pharmacology.
[10] Luca Toldo,et al. Extraction of potential adverse drug events from medical case reports , 2012, Journal of biomedical semantics.
[11] Paloma Martínez,et al. Detecting drugs and adverse events from Spanish social media streams , 2014, Louhi@EACL.
[12] Guodong Zhou,et al. Dependency-directed Tree Kernel-based Protein-Protein Interaction Extraction from Biomedical Literature , 2011, IJCNLP.
[13] Azadeh Nikfarjam,et al. Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.
[14] Jian Yang,et al. Towards Internet-Age Pharmacovigilance: Extracting Adverse Drug Reactions from User Posts in Health-Related Social Networks , 2010, BioNLP@ACL.
[15] M. Schuemie,et al. Combining electronic healthcare databases in Europe to allow for large‐scale drug safety monitoring: the EU‐ADR Project , 2011, Pharmacoepidemiology and drug safety.
[16] Ming Yang,et al. Filtering big data from social media - Building an early warning system for adverse drug reactions , 2015, J. Biomed. Informatics.
[17] Rong Xu,et al. Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing , 2013, BMC Bioinformatics.
[18] Bruce R. Schatz,et al. Measuring Population Health Using Personal Health Messages , 2009, AMIA.
[19] Mari Carmen Domingo,et al. Managing Healthcare through Social Networks , 2010, Computer.
[20] Sunghwan Sohn,et al. Drug side effect extraction from clinical narratives of psychiatry and psychology patients , 2011, J. Am. Medical Informatics Assoc..
[21] K. Bretonnel Cohen,et al. Mining FDA drug labels for medical conditions , 2013, BMC Medical Informatics and Decision Making.
[22] Paloma Martínez,et al. The DDI corpus: An annotated corpus with pharmacological substances and drug-drug interactions , 2013, J. Biomed. Informatics.
[23] Ophir Frieder,et al. A framework for detecting public health trends with Twitter , 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).
[24] Abeed Sarker,et al. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features , 2015, J. Am. Medical Informatics Assoc..
[25] Azadeh Nikfarjam,et al. Mining Twitter for Adverse Drug Reaction Mentions : A Corpus and Classification Benchmark , 2014 .
[26] Paloma Martínez,et al. Exploring Spanish health social media for detecting drug effects , 2015, BMC Medical Informatics and Decision Making.
[27] Taha A. Kass-Hout,et al. Digital Drug Safety Surveillance: Monitoring Pharmaceutical Products in Twitter , 2014, Drug Safety.
[28] P Ryan,et al. Novel Data‐Mining Methodologies for Adverse Drug Event Discovery and Analysis , 2012, Clinical pharmacology and therapeutics.
[29] Xindong Wu,et al. Twitter K-H networks in action: Advancing biomedical literature for drug search , 2015, J. Biomed. Informatics.
[30] Lyle H. Ungar,et al. Identifying potential adverse effects using the web: A new approach to medical hypothesis generation , 2011, J. Biomed. Informatics.
[31] Alan R. Aronson,et al. An overview of MetaMap: historical perspective and recent advances , 2010, J. Am. Medical Informatics Assoc..
[32] A. Kaplan,et al. Users of the world, unite! The challenges and opportunities of Social Media , 2010 .
[33] Christophe G. Lambert,et al. Bridging Islands of Information to Establish an Integrated Knowledge Base of Drugs and Health Outcomes of Interest , 2014, Drug Safety.
[34] C. Raehl,et al. Adverse Drug Reactions in United States Hospitals , 2006, Pharmacotherapy.
[35] Frederick Reiss,et al. Rule-Based Information Extraction is Dead! Long Live Rule-Based Information Extraction Systems! , 2013, EMNLP.
[36] Paloma Martínez,et al. An analysis on the entity annotations in biological corpora , 2014, F1000Research.
[37] Paloma Martínez,et al. Extracting drug indications and adverse drug reactions from Spanish health social media , 2014, BioNLP@ACL.
[38] Abdul Mateen Rajput,et al. Automatic detection of adverse events to predict drug label changes using text and data mining techniques , 2013, Pharmacoepidemiology and drug safety.
[39] P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .