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Quantifying the severity of adverse drug reactions using social media
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpt.2172openalex-snapshot
A New Era in Pharmacovigilance: Toward Real‐World Data and Digital Monitoring
inferredcites →https://doi.org/10.1002/cpt.944openalex-snapshot
Postmarket Safety Outcomes for New Molecular Entity (NME) Drugs Approved by the Food and Drug Administration Between 2002 and 2014
inferredcites →https://doi.org/10.1002/cpt1979254381openalex-snapshot
A scale for assessing the severity of diseases and adverse drug reactions; Application to drug benefit and risk
inferredcites →https://doi.org/10.1002/pds.1984openalex-snapshot
Adverse drug events in the outpatient setting: an 11‐year national analysis
inferredcites →https://doi.org/10.1002/pds.4155openalex-snapshot
Influence of age, sex and seriousness on reporting of adverse drug reactions in Sweden
inferredcites →https://doi.org/10.1016/j.eclinm.2019.10.001openalex-snapshot
Reported adverse drug reactions in women and men: Aggregated evidence from globally collected individual case reports during half a century
inferredcites →https://doi.org/10.1016/j.jbi.2015.11.004openalex-snapshot
Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use
inferredcites →https://doi.org/10.1016/j.jbi.2019.103307openalex-snapshot
RedMed: Extending drug lexicons for social media applications
inferredcites →https://doi.org/10.1016/j.patter.2020.100108openalex-snapshot
Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women
inferredcites →https://doi.org/10.1038/sdata.2017.167openalex-snapshot
A dataset quantifying polypharmacy in the United States
inferredcites →https://doi.org/10.1046/j.1525-1497.2003.20130.xopenalex-snapshot
Adverse drug event monitoring at the food and drug administration
inferredcites →https://doi.org/10.1093/jamia/ocu041openalex-snapshot
Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
inferredcites →https://doi.org/10.1093/nar/gkh061openalex-snapshot
The Unified Medical Language System (UMLS): integrating biomedical terminology
inferredcites →https://doi.org/10.1093/nar/gkv1075openalex-snapshot
The SIDER database of drugs and side effects
inferredcites →https://doi.org/10.1111/poms.12895openalex-snapshot
Shared Minds: How Patients Use Collaborative Information Sharing via Social Media Platforms
inferredcites →https://doi.org/10.1126/scitranslmed.3003377openalex-snapshot
Data-Driven Prediction of Drug Effects and Interactions
inferredcites →https://doi.org/10.1177/1060028018765159openalex-snapshot
Cost of Prescription Drug–Related Morbidity and Mortality
inferredcites →https://doi.org/10.1186/1471-2288-6-48openalex-snapshot
Joint distribution approaches to simultaneously quantifying benefit and risk
inferredcites →https://doi.org/10.1186/s12859-019-2628-5openalex-snapshot
Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA
inferredcites →https://doi.org/10.1214/aos/1176344552openalex-snapshot
Bootstrap Methods: Another Look at the Jackknife
inferredcites →https://doi.org/10.18653/v1/d16-1057openalex-snapshot
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora
inferredcites →https://doi.org/10.18653/v1/w17-2316openalex-snapshot
Detecting Personal Medication Intake in Twitter: An Annotated Corpus and Baseline Classification System
inferredcites →https://doi.org/10.2165/00002018-199920020-00002openalex-snapshot
The Medical Dictionary for Regulatory Activities (MedDRA)
inferredcites →https://doi.org/10.2165/00002018-200528100-00003openalex-snapshot
Clarification of Terminology in Drug Safety
inferredcites →https://doi.org/10.2165/00002018-200629050-00003openalex-snapshot
Under-Reporting of Adverse Drug Reactions
inferredcites →https://doi.org/10.2196/jmir.2741openalex-snapshot
An Exploration of Social Circles and Prescription Drug Abuse Through Twitter
inferredcites →https://doi.org/10.2196/jmir.3962openalex-snapshot
Ranking Adverse Drug Reactions With Crowdsourcing
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
inferredcites →https://doi.org/10.48550/arxiv.1607.00653openalex-snapshot
node2vec: Scalable Feature Learning for Networks
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1038/s41746-025-01642-xopenalex-snapshot
Monitoring the opioid epidemic via social media discussions
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