Filtering big data from social media - Building an early warning system for adverse drug reactions
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TLDR
The overall design of the system provides satisfactory performance in identifying ADR related posts for post-marketing drug surveillance and points out a potentially fruitful direction for building other early warning systems that need to filter big data from social media networks.About:
This article is published in Journal of Biomedical Informatics.The article was published on 2015-04-01 and is currently open access. It has received 133 citations till now. The article focuses on the topics: Social media mining & Supervised learning.read more
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Journal ArticleDOI
Big Data in Public Health: Terminology, Machine Learning, and Privacy.
Stephen J. Mooney,Vikas Pejaver +1 more
TL;DR: The ethical implications of the big data revolution with particular emphasis on maintaining appropriate care for privacy in a world in which technology is rapidly changing social norms regarding the need for (and even the meaning of) privacy are considered.
Journal ArticleDOI
Polarization and Fake News: Early Warning of Potential Misinformation Targets
TL;DR: In this article, the authors introduce a framework for promptly identifying polarizing content on social media and thus predicting future fake news topics, based on a series of characteristics related to users' behavior on online social media.
Journal ArticleDOI
Drug-drug interaction extraction from biomedical texts using long short-term memory network.
Sunil Kumar Sahu,Ashish Anand +1 more
TL;DR: In this paper, three LSTM-based models, namely B-LSTM, AB-LstM, and Joint AB-lstm, were proposed for drug-drug interaction (DDI) extraction.
Journal ArticleDOI
Social media and pharmacovigilance: A review of the opportunities and challenges
R. J. Sloane,Orod Osanlou,Orod Osanlou,David J. Lewis,Danushka Bollegala,Simon Maskell,Munir Pirmohamed,Munir Pirmohamed +7 more
TL;DR: Key challenges identifying relevant current research and possible solutions in addressing technical, regulatory and ethical challenges of adverse drug reactions are outlined.
Journal ArticleDOI
Text mining approach to predict hospital admissions using early medical records from the emergency department.
Filipe Rissieri Lucini,Flávio Sanson Fogliatto,Giovani J.C. da Silveira,Jeruza Lavanholi Neyeloff,Michel José Anzanello,Ricardo de Souza Kuchenbecker,Beatriz D'Agord Schaan +6 more
TL;DR: Text mining could provide valuable information and facilitate decision-making by inward bed management teams and could be used to manage daily routines in EDs such as capacity planning and resource allocation.
References
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