About: The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews
Creator	Alimova, Ilseyar Miftahutdinov, Zulfat Tutubalina, Elena Malykh, Valentin Nikolenko, Sergey Sakhovskiy, Andrey
Source	ArXiv
abstract	The Russian Drug Reaction Corpus (RuDReC) is a new partially annotated corpus of consumer reviews in Russian about pharmaceutical products for the detection of health-related named entities and the effectiveness of pharmaceutical products. The corpus itself consists of two parts, the raw one and the labelled one. The raw part includes 1.4 million health-related user-generated texts collected from various Internet sources, including social media. The labelled part contains 500 consumer reviews about drug therapy with drug- and disease-related information. Labels for sentences include health-related issues or their absence. The sentences with one are additionally labelled at the expression level for identification of fine-grained subtypes such as drug classes and drug forms, drug indications, and drug reactions. Further, we present a baseline model for named entity recognition (NER) and multi-label sentence classification tasks on this corpus. The macro F1 score of 74.85% in the NER task was achieved by our RuDR-BERT model. For the sentence classification task, our model achieves the macro F1 score of 68.82% gaining 7.47% over the score of BERT model trained on Russian data. We make the RuDReC corpus and pretrained weights of domain-specific BERT models freely available at https://github.com/cimm-kzn/RuDReC
has issue date	2020-04-07(xsd:dateTime)
has license	arxiv
sha1sum (hex)	9afed5a68ec147ddf221c9ae6c7ff8f0ceef2ef8
resource representing a document's title	The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews
resource representing a document's body	covid:9afed5a68ec147ddf221c9ae6c7ff8f0ceef2ef8#body_text
is schema:about of	named entity 'score' named entity 'drug' named entity 'pharmaceutical' named entity 'F1 score' named entity 'sentences' named entity 'Effectiveness' named entity 'XXXXX' named entity 'XXXXX' named entity 'HEALTH CONDITIONS' named entity 'SPECIFIC' named entity 'DISEASE' named entity 'SCORE' named entity 'ANALYSIS' named entity 'INFORMATION EXTRACTION' named entity 'RANGE' named entity 'CLASSES' named entity 'PARTIALLY' named entity 'VARIOUS' named entity 'TRAINED' named entity 'RESULTS' named entity 'MOTIVATION' named entity 'APPLICATIONS' named entity 'COLLECTED' named entity 'GENERATED' named entity 'RELATED' named entity 'ROLE' named entity 'LABEL' named entity 'INCLUDING' named entity 'CONSUMER' named entity 'INFORMATION' named entity 'SENTENCE CLASSIFICATION' named entity 'AGGREGATING' named entity 'ABOUT' named entity 'REVIEWS' named entity '27S' named entity 'DRUG' named entity 'GAINING' named entity 'REPORTED' named entity 'INCLUDES' named entity 'DRUG REACTIONS' named entity 'effectiveness' named entity 'macro' named entity 'drug therapy' named entity 'languages' named entity 'F1 score' named entity 'github.com' named entity 'indications' named entity 'Availability' named entity 'products' named entity 'macro' named entity 'Drugs' named entity 'Russian' named entity 'sentences' named entity 'extraction' named entity 'detection' named entity 'F1 score' named entity 'Russian language' named entity 'text mining' named entity 'information extraction' named entity 'biomedical research' named entity 'Internet' named entity 'XXXXX' named entity 'Associate Editor' named entity 'web portal' named entity 'adverse reactions' named entity 'Russia' named entity 'UGTs' named entity 'UGTs' named entity 'sequence labeling' named entity 'web page' named entity 'named entity recognition' named entity 'pharmacovigilance' named entity 'drug reactions' named entity 'influenza' named entity 'social network' named entity 'Twitter' named entity 'Conditional Random Fields' named entity 'Kazan Federal University' named entity 'MedDRA' named entity 'nootropics' named entity 'Lipitor' named entity 'Medical Subject Headings'

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