Postmarket drug surveillance without trial costs: discovery of adverse drug reactions through large-scale analysis of web search queries - Wikidata - awgldk - TriplyDB

Postmarket drug surveillance without trial costs: discovery of adverse drug reactions through large-scale analysis of web search queries

Postmarket drug surveillance without trial costs: discovery of adverse drug reactions through large-scale analysis of web search queries

http://www.wikidata.org/entity/Q28677138

about

A curated and standardized adverse drug event resource to accelerate drug safety research Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis Information is in the eye of the beholder: Seeking information on the MMR vaccine through an Internet search engine Automatic identification of Web-based risk markers for health events Detecting disease outbreaks in mass gatherings using Internet data Cumulative query method for influenza surveillance using search engine data Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS.Mining adverse drug reactions from online healthcare forums using hidden Markov model Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration's Adverse Event Reporting System Narratives.Role of Pharmacovigilance in India: An overview.Using Web-Based Search Data to Study the Public's Reactions to Societal Events: The Case of the Sandy Hook Shooting In silico methods for drug repurposing and pharmacology An exploration of social circles and prescription drug abuse through Twitter.Patient perspectives of dabigatran: analysis of online discussion forums.Internet search patterns of human immunodeficiency virus and the digital divide in the Russian Federation: infoveillance study.Predicting Drug Recalls From Internet Search Engine Queries.From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources.Identifying Complementary and Alternative Medicine Usage Information from Internet Resources. A Systematic Review Analyzing search behavior of healthcare professionals for drug safety surveillance.Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews.Adverse Reactions Associated With Cannabis Consumption as Evident From Search Engine Queries.Evidence From Web-Based Dietary Search Patterns to the Role of B12 Deficiency in Non-Specific Chronic Pain: A Large-Scale Observational Study.[Patterns of access to information on protection against UV during the Brazilian summer: is there such a thing as the "summer effect"?].Detection of Adverse Drug Reactions using Medical Named Entities on Twitter.Respiratory syncytial virus tracking using internet search engine data.Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review.

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P2860

Postmarket drug surveillance without trial costs: discovery of adverse drug reactions through large-scale analysis of web search queries

http://www.wikidata.org/entity/Q28677138

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2013 nî lūn-bûn

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2013 թուականի Յունիսին հրատարակուած գիտական յօդուած

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2013 թվականի հունիսին հրատարակված գիտական հոդված

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2013年の論文

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Journal of Medical Internet Research

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Evgeniy Gabrilovich

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P2860

Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet

Withdrawal of cerivastatin from the world market

Detecting influenza epidemics using search engine query data

Natural supplements for H1N1 influenza: retrospective observational infodemiology study of information and search activity on the Internet

A side effect resource to capture phenotypic effects of drugs

Application of data mining techniques in pharmacovigilance.

The return of thalidomide: can birth defects be prevented?

Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA's spontaneous reports database.

Validation of a common data model for active safety surveillance research.

Failing the public health--rofecoxib, Merck, and the FDA.

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