9,053 Hits in 5.5 sec

Evaluation of Linked, Open Data Sources for Mining Adverse Drug Reaction Signals [chapter]

Pantelis Natsiavas, Nicos Maglaveras, Vassilis Koutkias
2017 Lecture Notes in Computer Science  
In this work, we explore the capacity of open, linked data sources to assess adverse drug reaction (ADR) signals.  ...  Our study is based on a set of drugrelated Bio2RDF data sources and three reference datasets, containing both positive and negative ADR signals, which were used for benchmarking.  ...  This research has been partially funded from the European Union's Horizon 2020 Framework Programme for Research and Innovation Action under Grant Agreement no. 643491 (the PATHway project).  ... 
doi:10.1007/978-3-319-70284-1_24 fatcat:5rbggp7hzvch3hxhhlbsacz7ra

Application of data mining techniques in pharmacovigilance

Andrew M. Wilson, Lehana Thabane, Anne Holbrook
2003 British Journal of Clinical Pharmacology  
Aims To discuss the potential use of data mining and knowledge discovery in databases for detection of adverse drug events (ADE) in pharmacovig ilance.  ...  Methods A literature search was conducted to identify articles, which contained details of data mining, signal generation or knowledge discovery in relation to adverse drug reactions or pharmacovigilance  ...  [40] have demonstrated the use of the BCPNN Data Mining approach to detect signals of specific adverse drug reactions and also adverse events as a drug class effect.  ... 
doi:10.1046/j.1365-2125.2003.01968.x pmid:14748811 pmcid:PMC1884444 fatcat:6j7wgbd3mbbqrccrhxhxjwyeoi

Harnessing scientific literature reports for pharmacovigilance

Anna Ripple, Joseph Tonning, Monica Munoz, Rashedul Hasan, Thomas Ly, Henry Francis, Olivier Bodenreider, Alfred Sorbello
2017 Applied Clinical Informatics  
Methods: A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and  ...  We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining.  ...  Pucino for their support of the development of this prototype tool. Research Article Result linked to source of information Spreadsheet Inventory  ... 
doi:10.4338/aci-2016-11-ra-0188 pmid:28326432 pmcid:PMC5373771 fatcat:ml26yskqyfan5dh6lhhbd3ttii

Data Mining Techniques in Pharmacovigilance: Analysis of the Publicly Accessible FDA Adverse Event Reporting System (AERS) [chapter]

Elisabetta Poluzzi, Emanuel Raschi, Carlo Piccinni, Fabrizio De
2012 Data Mining Applications in Engineering and Medicine  
Data Mining Techniques in Pharmacovigilance: Analysis of the Publicly Accessible FDA Adverse Event Reporting System (AERS) 267 tools makes them valuable sources for data mining aimed to address clinical  ...  strictly related to drug use (namely, adverse drug reactions) and patho-physiological plausibility supporting drug-reaction associations should be more stringently verified. complements disproportionality  ...  Acknowledgments We thank Ariola Koci, statistician working at the Department of Medical and Surgical Sciences, University of Bologna for assistance in data management.  ... 
doi:10.5772/50095 fatcat:clp3ldmcqfg5fbst7q2pbgs7xm

Combining Social Media and FDA Adverse Event Reporting System to Detect Adverse Drug Reactions

Ying Li, Antonio Jimeno Yepes, Cao Xiao
2020 Drug Safety  
Adverse drug reactions (ADRs) are unintended reactions caused by a drug or combination of drugs taken by a patient.  ...  data sources.  ...  Fig. 1 1 Processing pipeline for generating, combining and evaluating adverse drug reaction signals produced by Twitter, FAERS, and the combined system.  ... 
doi:10.1007/s40264-020-00943-2 pmid:32385840 fatcat:sixjtosd45fvzhakdi25am3eu4

Bridging Islands of Information to Establish an Integrated Knowledge Base of Drugs and Health Outcomes of Interest

Richard D. Boyce, Patrick B. Ryan, G. Niklas Norén, Martijn J. Schuemie, Christian Reich, Jon Duke, Nicholas P. Tatonetti, Gianluca Trifirò, Rave Harpaz, J. Marc Overhage, Abraham G. Hartzema, Mark Khayter (+4 others)
2014 Drug Safety  
The workgroup's mission is to develop an open-source standardized knowledge base for the effects of medical products and an efficient procedure for maintaining and expanding it.  ...  This presents an opportunity to establish an open-source community effort to develop a global knowledge base, one that brings together and standardizes all available information for all drugs and all health  ...  Also, we will use a text mining tool called SPLICER to extract adverse event information present in the boxed warnings, warning/precaution, and adverse reaction sections of SPLs, and link the extracted  ... 
doi:10.1007/s40264-014-0189-0 pmid:24985530 pmcid:PMC4134480 fatcat:j5hqrmbkyjamdhnzo7bdse3vfu

Social media mining for drug safety signal detection

Christopher C. Yang, Haodong Yang, Ling Jiang, Mi Zhang
2012 Proceedings of the 2012 international workshop on Smart health and wellbeing - SHB '12  
Consequently, it is difficult to detect the adverse drug reactions signals in a timely manner.  ...  Many of this online discussion involve adverse drug reactions.  ...  the ADR signals for each pair of drug and adverse reaction.  ... 
doi:10.1145/2389707.2389714 dblp:conf/cikm/YangYJZ12 fatcat:lm6fnmrsabgk5mq33pnsr5exou

Mechanism-based Pharmacovigilance over the Life Sciences Linked Open Data Cloud

Maulik R Kamdar, Mark A Musen
2018 AMIA Annual Symposium Proceedings  
Adverse drug reactions (ADR) result in significant morbidity and mortality in patients, and a substantial proportion of these ADRs are caused by drug-drug interactions (DDIs).  ...  We integrate data and knowledge from four different sources using Semantic Web Technologies and Linked Data principles to generate a systems network.  ...  The authors also acknowledge Michel Dumontier for his help using Bio2RDF linked data. This work is supported by Grant HG004028 from the US National Institutes of Health.  ... 
pmid:29854169 pmcid:PMC5977627 fatcat:lvr422wxana2hh5zkeyik67axa

Page 133 of British Journal of Clinical Pharmacology Vol. 57, Issue 2 [page]

2004 British Journal of Clinical Pharmacology  
Effects of coding dictionary on signal generation 1 Pirmohamed M, Breckenridge AM, Kitteringham NR consideration of use of MedDRA compared with WHO- Adverse drug reactions.  ...  However, by being open minded, it is possible to search for many different ADEs at once.  ... 

A Survey of the FDA's Adverse Event Reporting System Database Concerning Urogenital Tract Infections and Sodium Glucose Cotransporter‐2 Inhibitor Use

Juan Shen, Jincheng Yang, Bin Zhao
2019 Diabetes Therapy  
On the basis of 37,100 reports, 1628 reports (4.39% of total adverse drug reactions, ADRs) were associated with UTIs; among them, the number of UTIs reported for the top four was as follows: canagliflozin  ...  Disproportionality analysis and Bayesian analysis were used to mine FAERS for suspected UTI data for SGLT-2i use from the first quarter of 2004 to the second quarter of 2018.  ...  All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given  ... 
doi:10.1007/s13300-019-0611-9 pmid:30953300 pmcid:PMC6531563 fatcat:palcqze3pjahznbpgbu3kpwura

A corpus for mining drug-related knowledge from Twitter chatter: Language models and their utilities

Abeed Sarker, Graciela Gonzalez
2017 Data in Brief  
Using this data, which is rich in drug-related chatter, we developed language models to aid the development of data mining tools and methods in this domain.  ...  The data set we are releasing consists of 267,215 Twitter posts made during the fourmonth period-November, 2014 to February, 2015. The posts mention over 250 drug-related keywords.  ...  Fig. 4 illustrates similar findings for this drug as well, with strong signals for the five known adverse reaction terms to the left.  ... 
doi:10.1016/j.dib.2016.11.056 pmid:27981203 pmcid:PMC5144647 fatcat:ylcm5fot3jhplilxh6jcfyj25q

Signal Detection of Drug Complications Applying Association Rule Learning for Stevens-Johnson Syndrome

Yuko Shirakuni, Kousuke Okamoto, Norihito Kawashita, Teruo Yasunaga, Tatsuya Takagi
2009 Journal of Computer Aided Chemistry  
We defined new value K for the evaluation of existing signal detection. Association rule was evaluated according to criterion K value.  ...  Our purpose is to propose an efficient procedure that enables the detection of signals for drugs related to an adverse event, without assuming the involvement of a specific drug.  ...  SOURCE 163,505 THERAPY DATA 163,890 INDICATIONS FOR USE 187,453 *: Supplemental reports are not included.  ... 
doi:10.2751/jcac.10.118 fatcat:e7jcdnftzjhe5a2dmhqkgyffza

Pharmacovigilance analysis of adverse event reports for aliskiren hemifumarate, a first-in-class direct renin inhibitor

Ayad Ali
2011 Therapeutics and Clinical Risk Management  
Data mining also enables detection of safety signals for drug-event combinations that might go undetected in a massive database because of the vast number of drugs 343 Adverse events with aliskiren  ...  MgPs data mining algorithm It is impractical and valueless to quantify the risk of adverse drug reactions reported in the AERS utilizing conventional analysis methods, because of the inaccurate number  ... 
doi:10.2147/tcrm.s23889 pmid:21941439 pmcid:PMC3176166 fatcat:ovivodahcbbefeaociva4iffzm

tcTKB: an integrated cardiovascular toxicity knowledge base for targeted cancer drugs

Rong Xu, QuanQiu Wang
2015 AMIA Annual Symposium Proceedings  
The data sources include FDA drug labels (44,979 labels), the FDA Adverse Event Reporting System (FAERS) (4,285,097 records), the Canada Vigilance Adverse Reaction Online Database (CVAROD) (1,107,752 records  ...  In this study, we built tcTKB, a comprehensive CV toxicity knowledge base for targeted cancer drugs, by extracting drug-CV pairs from five large-scale and complementary data sources.  ...  We would like to thank the three curators from ThinTek for the manual curation.  ... 
pmid:26958275 pmcid:PMC4765587 fatcat:geujs4hwl5bzvbzds3ai6a6ob4

Harnessing Social Media for Drug-Drug Interactions Detection

Haodong Yang, Christopher C. Yang
2013 2013 IEEE International Conference on Healthcare Informatics  
Adverse drug reactions (ADRs) are causing a substantial amount of hospital admissions and deaths, which cannot be underestimated.  ...  Currently, DDIs detection mainly depends on four kinds of data sources -clinical trial data, spontaneous reporting systems, electronic medical records, and chemical/pharmacologic databases, all of which  ...  detecting signals of adverse drug reactions [2, 13] .  ... 
doi:10.1109/ichi.2013.10 dblp:conf/ichi/YangY13 fatcat:eyet3l7tvjfihiz37hwmy6ymoe
« Previous Showing results 1 — 15 out of 9,053 results