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Adverse event detection by integrating twitter data and VAERS

Junxiang Wang, Liang Zhao, Yanfang Ye, Yuji Zhang
2018 Journal of Biomedical Semantics  
data and the Vaccine Adverse Event Reporting System (VAERS) information aiming to identify potential AEs after influenza vaccine.  ...  Results: To tackle both challenges from traditional reporting systems and social media, we exploit their complementary strength and develop a combinatorial classification approach by integrating Twitter  ...  VAERS: Vaccine Adverse Event Reporting System.  ... 
doi:10.1186/s13326-018-0184-y pmid:29925405 pmcid:PMC6011255 fatcat:fz4t7rv6kzdopo3x4fmageid5y

Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data

Andrew T. Lian, Jingcheng Du, Lu Tang
2022 Vaccines  
The goal of this project is to develop a machine learning and natural language processing approach to identify COVID-19 vaccine adverse events (VAE) from Twitter data.  ...  To the best of our knowledge, this is the first study to identify COVID-19 vaccine adverse event signals from social media.  ...  We also thank Meng Zhang and Jingna Feng for the Twitter data annotation. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/vaccines10010103 pmid:35062764 pmcid:PMC8781534 fatcat:fwszstfmercwhkyb43itslahga

Multi-instance Domain Adaptation for Vaccine Adverse Event Detection [article]

Junxiang Wang, Liang Zhao
2020 arXiv   pre-print
Detection of vaccine adverse events is crucial to the discovery and improvement of problematic vaccines.  ...  Case studies showed that formal reports and extracted adverse-relevant tweets by MIDA shared a similarity of keyword and description patterns.  ...  Dataset Description The task of the first dataset is to detect whether Twitter users are affected by adverse event according to their tweets. The dataset consists of Twitter data and formal reports.  ... 
arXiv:2009.04901v1 fatcat:zlerjhizzbboxg3jdigdte3bzq

Multi-instance Domain Adaptation for Vaccine Adverse Event Detection

Junxiang Wang, Liang Zhao
2018 Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18  
Detection of vaccine adverse events is crucial to the discovery and improvement of problematic vaccines.  ...  Case studies showed that formal reports and extracted adverse-relevant tweets by MIDA shared a similarity of keyword and description patterns.  ...  Dataset Description The task of the first dataset is to detect whether Twitter users are affected by adverse event according to their tweets. The dataset consists of Twitter data and formal reports.  ... 
doi:10.1145/3178876.3186051 dblp:conf/www/Wang018 fatcat:w4mgqwhdenhdnoi74vv7fndt4e

Vaccine Safety Resources for Nurses

Elaine R. Miller, Tom T. Shimabukuro, Beth F. Hibbs, Pedro L. Moro, Karen R. Broder, Claudia Vellozzi
2015 The American Journal of Nursing  
VSD data can be used to detect safety problems and to assess and quantify the risk of adverse events. 15 A VSD study was able to quantify the risk of anaphylaxis following vaccination in general in children  ...  Datalink (VSD) uses electronic health record data from nine integrated health care organizations to conduct surveillance and epidemiologic studies.  ... 
doi:10.1097/01.naj.0000470404.74424.ee pmid:26222474 pmcid:PMC4599699 fatcat:j2757fs5mzhvjfimkd4s7kdfo4

Vaccine Safety [chapter]

Frank Destefano, Paul A. Offit, Allison Fisher
2018 Plotkin's Vaccines  
Acknowledgments We are grateful to Robert Davis, Deborah Gust, Robert Chen, and Charles Hackett who contributed sections of this chapter in previous editions of this book.  ...  Initial safety data were provided by VAERS, which found that the adverse event profile after 2009-H1N1 vaccine in VAERS (>10,000 reports) was consistent with that of seasonal influenza vaccines. 91, 138  ...  [83] [84] [85] Some increases in adverse events detected by VAERS might not be true increases, but instead might be the result of increases in reporting efficiency or vaccine coverage.  ... 
doi:10.1016/b978-0-323-35761-6.00082-1 fatcat:opzmvotoqfgyjjy5bmgni2opju

Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches

Pantelis Natsiavas, Andigoni Malousi, Cédric Bousquet, Marie-Christine Jaulent, Vassilis Koutkias
2019 Frontiers in Pharmacology  
The collected data illustrate the use of KE for various DS aspects, such as Adverse Drug Event (ADE) information collection, detection, and assessment.  ...  Various exemplar applications were identified with promising results, e.g., improvement in Adverse Drug Reaction (ADR) prediction, detection of drug interactions, and novel ADE profiles related with specific  ...  The collected data illustrate the use of KE for various DS aspects, such as Adverse Drug Event (ADE) information collection, detection, and assessment.  ... 
doi:10.3389/fphar.2019.00415 pmid:31156424 pmcid:PMC6533857 fatcat:pljcyqcp6red7pdwa5burxgbx4

Big Data and Pharmacovigilance: Data Mining for Adverse Drug Events and Interactions

C Lee Ventola
2018 P & T : a peer-reviewed journal for formulary management  
A "big data" approach to pharmacovigilance involves the identification of drug-ADE associations by data mining various electronic sources, including: adverse event reports, the medical literature, electronic  ...  Adverse drug events (ADEs), including drug interactions, have a tremendous impact on patient health and generate substantial health care costs.  ...  Event Text Mining (VaeTM) system to detect drug-ADE associations present in the text in the SRS database that it maintains for vaccines, the Vaccine Adverse Event Reporting System (VAERS). 2 This software  ... 
pmid:29896033 pmcid:PMC5969211 fatcat:rpjrb2p2rngdtd4ap6yaqr2rtq

Evolving Roles of Spontaneous Reporting Systems to Assess and Monitor Drug Safety [chapter]

Emanuel Raschi, Ugo Moretti, Francesco Salvo, Antoine Pariente, Ippazio Cosimo Antonazzo, Fabrizio De Ponti, Elisabetta Poluzzi
2018 Pharmacovigilance [Working Title]  
Post-marketing data sources Not only notification of suspected adverse drug events is mandatory for health professionals, but also other subjects can report events to the relevant regulatory authorities  ...  After a panorama on key data sources and analyses of post-marketing data of adverse drug reactions, a critical appraisal of methodological issues and debated future applications of SRSs will be presented  ...  /cdrh/cfdocs/cfMAUDE/search.CFM), VAERS-Vaccines Adverse Event Reporting System (https://vaers.hhs.gov/data/datasets.html), and CAERS-Center for Food Safety and Applied Nutrition Adverse Event Reporting  ... 
doi:10.5772/intechopen.79986 fatcat:bguoxablmzbqxhqilyfxeltbwi

Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is ("Isolate–Inactivate–Inject") Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview

Nicola Luigi Bragazzi, Vincenza Gianfredi, Milena Villarini, Roberto Rosselli, Ahmed Nasr, Amr Hussein, Mariano Martini, Masoud Behzadifar
2018 Frontiers in Public Health  
This shift has been possible thanks to Big Data, characterized by different dimensions, such as high volume, velocity, and variety of data.  ...  role to a science, characterized by a rational design and plan ("vaccinology 3.0").  ...  side effects Vaccine adverse event reporting system (VAERS) Vaccine adverse event ontology Adversomics Digital epidemiology/infodemiology and infoveillance Vaccine literacy/vaccine hesitancy  ... 
doi:10.3389/fpubh.2018.00062 pmid:29556492 pmcid:PMC5845111 fatcat:ctinubftg5gdnniwdmzj26gura

Detecting Epidemic Diseases Using Sentiment Analysis of Arabic Tweets

Qanita Baker, Farah Shatnawi, Saif Rawashdeh, Mohammad Al-Smadi, Yaser Jararweh
2020 Journal of universal computer science (Online)  
In this study, a new approach is proposed in order to detect Influenza using machine learning techniques from Arabic tweets in Arab countries.  ...  Opinion mining is an important step towards facilitating information in health data. Several studies have demonstrated the possibility of tracking diseases using public tweets.  ...  Acknowledgment Thanks to Jordan University of Science and Technology for supporting this publication under Award Number 20170030.  ... 
doi:10.3897/jucs.2020.004 fatcat:kcfhy26parc2pgykpwm33jw4ba

International Society for Disease Surveillance Conference 2010

D.G. Cochrane, J.R. Allegra
2011 Emerging Health Threats Jour  
Using Twitter to estimate H1N1 influenza activity A Signorini, PM Polgreen, and AM Segre 84.  ...  A comparison of syndromic surveillance chief complaint data and discharge data in a pediatric hospital system during 2009 H1N1 D Peace, W Smith, A Reeves, D Little, K Soetebier, and C Drenzek 89.  ...  Disclaimer The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.  ... 
doi:10.3402/ehtj.v4i0.7174 pmid:24149039 pmcid:PMC3168218 fatcat:r34ofgptjbhbblmg7k2xwtcxkq

An ensemble of neural models for nested adverse drug events and medication extraction with subwords

2019 JAMIA Journal of the American Medical Informatics Association  
To better represent rare and unknown words in entities, we further tokenized the MIMIC III data set by splitting the words into finer-grained subwords.  ...  This article describes an ensembling system to automatically extract adverse drug events and drug related entities from clinical narratives, which was developed for the 2018 n2c2 Shared Task Track 2.  ...  ACKNOWLEDGMENTS The authors thank Artificial Intelligence Research Centre (AIRC), National Institute of Advanced Industrial Science and Technology (AIST) for the computational resources.  ... 
doi:10.1093/jamia/ocz075 pmid:31197355 pmcid:PMC6913208 fatcat:dl3zf6p5vjhsff7trbclyh2bfq

Prevention and control of HPV infection and HPV-related cancers in Colombia- a meeting report

Alex Vorsters, Francesc Xavier Bosch, Paolo Bonanni, Eduardo L. Franco, Marc Baay, Clarissa Simas, Dur-e-Nayab Waheed, Carlos Castro, Raul Murillo, Lina Trujillo, Carolina Wiesner, Nubia Muñoz
2020 BMC Proceedings  
In response to drastic drop of vaccine coverage following the adverse event crisis in Carmen del Bolivar, Colombia, the HPV Prevention and Control Board in collaboration with the Colombian National Cancer  ...  The conclusion of the meeting included following suggestions to strengthen HPV prevention and control: 1) Re-introducing school-based vaccine programs, 2) Integrating primary and secondary prevention programs  ...  Acknowledgements We thank the session chairs and speakers for their valuable slides, presentations, and comments; and the meeting participants for their thorough and insightful discussions.  ... 
doi:10.1186/s12919-020-00192-2 pmid:32577128 pmcid:PMC7307134 fatcat:ioldqqc7zvg53cbrrasctcguzm

Identifying Cases of Shoulder Injury Related to Vaccine Administration (SIRVA) Using Natural Language Processing [article]

Chengyi Zheng, Jonathan Duffy, In-Lu Amy Liu, Lina S. Sy, Ronald A. Navarro, Sunhea S. Kim, Denison Ryan, Wansu Chen, Lei Qian, Cheryl Mercado, Steven J. Jacobsen
2021 medRxiv   pre-print
The NLP algorithm can potentially be used in future population-based studies to identify this rare adverse event, avoiding labor-intensive chart review validation.  ...  Methods: We conducted the study among members of a large integrated health care organization who were vaccinated between 04/1/2016 and 12/31/2017 and had subsequent diagnosis codes indicative of shoulder  ...  , including the clinical notes of the study subjects, Vaccine Adverse Event Reporting System (VAERS) reports [31] , ontologies (e.g., Unified Medical Language System (UMLS) [32] ), semantic lexicons  ... 
doi:10.1101/2021.05.05.21256555 fatcat:kepivcrkkfdyhjlpxlor3vtpxm
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