Cadec: A corpus of adverse drug event annotations

[Display omitted] •Introduction of CADEC an annotated corpus of consumer reviews in pharmacovigilance.•A review and comparison of available relevant resources.•Challenges and lessons from the process of creating such resources. CSIRO Adverse Drug Event Corpus (Cadec) is a new rich annotated corpus o...

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Veröffentlicht in:Journal of biomedical informatics Jg. 55; S. 73 - 81
Hauptverfasser: Karimi, Sarvnaz, Metke-Jimenez, Alejandro, Kemp, Madonna, Wang, Chen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Elsevier Inc 01.06.2015
Schlagworte:
Adverse drug reaction
Adverse Drug Reaction Reporting Systems - organization & administration
Annotated corpus
Annotations
Consumer Health Information - organization & administration
Consumer reviews
Data Mining - methods
Datasets as Topic - statistics & numerical data
Digital media
Drug safety
Drug-Related Side Effects and Adverse Reactions - classification
Drug-Related Side Effects and Adverse Reactions - epidemiology
Drugs
Grammars
Guidelines
Guidelines as Topic
Humans
Information extraction
Information retrieval
Machine Learning
MedDRA
Medical forum
Natural Language Processing
SNOMED CT
Social media
Social Media - classification
Social Media - organization & administration
Social networks
Terminology as Topic
Texts
Vocabulary, Controlled
SNOMED CT
Consumer reviews
MedDRA
Social media
Medical forum
Annotated corpus
Information extraction
Adverse drug reaction
Drug safety
ISSN:1532-0464, 1532-0480
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Zusammenfassung:[Display omitted] •Introduction of CADEC an annotated corpus of consumer reviews in pharmacovigilance.•A review and comparison of available relevant resources.•Challenges and lessons from the process of creating such resources. CSIRO Adverse Drug Event Corpus (Cadec) is a new rich annotated corpus of medical forum posts on patient-reported Adverse Drug Events (ADEs). The corpus is sourced from posts on social media, and contains text that is largely written in colloquial language and often deviates from formal English grammar and punctuation rules. Annotations contain mentions of concepts such as drugs, adverse effects, symptoms, and diseases linked to their corresponding concepts in controlled vocabularies, i.e., SNOMED Clinical Terms and MedDRA. The quality of the annotations is ensured by annotation guidelines, multi-stage annotations, measuring inter-annotator agreement, and final review of the annotations by a clinical terminologist. This corpus is useful for studies in the area of information extraction, or more generally text mining, from social media to detect possible adverse drug reactions from direct patient reports. The corpus is publicly available at https://data.csiro.au.1The data can be used for research purposes only, under the CSIRO data licence.1
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1532-0464
1532-0480
DOI:10.1016/j.jbi.2015.03.010