Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions

By R. Harpaz, Santiago Vilar, William DuMouchel, H. Salmasian, Krystl Haerian, Nigam H. Shah, H. Chase, Carol Friedman. 2013

171 citations recorded by the source corpus.

Subfields: Pharmacology, Statistics and Probability, Toxicology

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In Pharmacology

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Citations in the corpus

Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review (2017, methodology): “Harpaz et al. [7] used MedLEE to process discharge summaries, admission notes, and outpatient ofﬁce visit notes.”
Portable Automatic Text Classification for Adverse Drug Reaction Detection via Multi-corpus Training (2014, background): “…focused on combining information from multiple sources such as the combination/enrichment of information gathered from spontaneous reporting systems with literature findings [19, 20, 21], electronic health records [18], and chemical similarity [22], and even user posted data on social media [21].”
Bridging semantics and syntax with graph algorithms —state-of-the-art of extracting biomedical relations (2015, background): “These systems often explore the relations between drugs, genes and pathways, and discover ADRs [47–49] and DDIs [50,51] stated in text.”
Detection of drug‐drug interactions through data mining studies using clinical sources, scientific literature and social media (2018, unknown): “Besides underreporting, other phenomena include overreporting or reporting duplicity, limited demographic data or failing to provide the number of patients treated with a particular drug [142, 143].”
Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task (2016, methodology): “More recently, a similar set of computational methods has been applied to a number of diverse datasets such as the FDA’s Adverse Event Reporting System (FAERS) (12), electronic medical records (13), tweets, and user comments in social media (14).”
Linking Biochemical Pathways and Networks to Adverse Drug Reactions (2014, background): “[8] proposed a “signal-detection strategy” that combines the adverse event reporting system (AERS) of the USA Food and Drug Administration (FDA) and electronic health records (EHRs) for detection of ADRs.”