{"id":"https://openalex.org/W2966852993","doi":"https://doi.org/10.18653/v1/p19-2058","title":"Detecting Adverse Drug Reactions from Biomedical Texts with Neural Networks","display_name":"Detecting Adverse Drug Reactions from Biomedical Texts with Neural Networks","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2966852993","doi":"https://doi.org/10.18653/v1/p19-2058","mag":"2966852993"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-2058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-2058","pdf_url":"https://www.aclweb.org/anthology/P19-2058.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-2058.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019116960","display_name":"Ilseyar Alimova","orcid":"https://orcid.org/0000-0003-4528-6631"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]},{"id":"https://openalex.org/I2800906181","display_name":"St. Petersburg Department of Steklov Institute of Mathematics","ror":"https://ror.org/030h9s280","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I2800906181","https://openalex.org/I4210124601"]},{"id":"https://openalex.org/I4210141363","display_name":"Samsung (Russia)","ror":"https://ror.org/051an6p98","country_code":"RU","type":"company","lineage":["https://openalex.org/I4210141363"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Ilseyar Alimova","raw_affiliation_strings":["Kazan Federal University, Kazan, Russia","Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]},{"raw_affiliation_string":"Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia","institution_ids":["https://openalex.org/I4210141363","https://openalex.org/I2800906181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012311258","display_name":"Elena Tutubalina","orcid":"https://orcid.org/0000-0001-7936-0284"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]},{"id":"https://openalex.org/I2800906181","display_name":"St. Petersburg Department of Steklov Institute of Mathematics","ror":"https://ror.org/030h9s280","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I2800906181","https://openalex.org/I4210124601"]},{"id":"https://openalex.org/I4210141363","display_name":"Samsung (Russia)","ror":"https://ror.org/051an6p98","country_code":"RU","type":"company","lineage":["https://openalex.org/I4210141363"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Elena Tutubalina","raw_affiliation_strings":["Kazan Federal University, Kazan, Russia","Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]},{"raw_affiliation_string":"Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia","institution_ids":["https://openalex.org/I4210141363","https://openalex.org/I2800906181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3993,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.5433213,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"415","last_page":"421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9735000133514404,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9510999917984009,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.64457106590271},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5556304454803467},{"id":"https://openalex.org/keywords/drug-reaction","display_name":"Drug reaction","score":0.551479160785675},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.5284911394119263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33765214681625366},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.20353755354881287},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.13165438175201416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.64457106590271},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5556304454803467},{"id":"https://openalex.org/C2993432071","wikidata":"https://www.wikidata.org/wiki/Q45959","display_name":"Drug reaction","level":3,"score":0.551479160785675},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.5284911394119263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33765214681625366},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.20353755354881287},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.13165438175201416}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-2058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-2058","pdf_url":"https://www.aclweb.org/anthology/P19-2058.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-2058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-2058","pdf_url":"https://www.aclweb.org/anthology/P19-2058.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G2322571202","display_name":null,"funder_award_id":"18-11-00284","funder_id":"https://openalex.org/F4320324099","funder_display_name":"Russian Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320324099","display_name":"Russian Science Foundation","ror":"https://ror.org/03y2gwe85"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966852993.pdf","grobid_xml":"https://content.openalex.org/works/W2966852993.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W77667794","https://openalex.org/W93323284","https://openalex.org/W290714361","https://openalex.org/W1678908053","https://openalex.org/W1901558184","https://openalex.org/W1987581851","https://openalex.org/W2007628554","https://openalex.org/W2013993544","https://openalex.org/W2071478164","https://openalex.org/W2101013878","https://openalex.org/W2102742655","https://openalex.org/W2118415328","https://openalex.org/W2131546905","https://openalex.org/W2159356691","https://openalex.org/W2171469118","https://openalex.org/W2265846598","https://openalex.org/W2396593442","https://openalex.org/W2460863069","https://openalex.org/W2515436458","https://openalex.org/W2562607067","https://openalex.org/W2574184737","https://openalex.org/W2610937402","https://openalex.org/W2779179495","https://openalex.org/W2787404918","https://openalex.org/W2792564858","https://openalex.org/W2798576649","https://openalex.org/W2893928366","https://openalex.org/W2897882775","https://openalex.org/W2905598915","https://openalex.org/W2907279416","https://openalex.org/W2916076862","https://openalex.org/W2933057087","https://openalex.org/W2963025814","https://openalex.org/W2963909901","https://openalex.org/W2964164368","https://openalex.org/W2964236337","https://openalex.org/W2964269444","https://openalex.org/W3100512753","https://openalex.org/W4285719527","https://openalex.org/W4301054811"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W111277538","https://openalex.org/W2544208578","https://openalex.org/W2044946730","https://openalex.org/W2377651601","https://openalex.org/W2378947884"],"abstract_inverted_index":{"Detection":[0],"of":[1,39,46,69,77,84],"adverse":[2,40],"drug":[3,41],"reactions":[4,42],"in":[5,75],"postapproval":[6],"periods":[7],"is":[8],"a":[9,25,61],"crucial":[10],"challenge":[11],"for":[12,27],"pharmacology.":[13],"Social":[14],"media":[15],"and":[16,53,65],"electronic":[17],"clinical":[18],"reports":[19],"are":[20],"becoming":[21],"increasingly":[22],"popular":[23],"as":[24,60],"source":[26],"obtaining":[28],"healthrelated":[29],"information.":[30],"In":[31],"this":[32],"work,":[33],"we":[34],"focus":[35],"on":[36,87],"extraction":[37],"information":[38],"from":[43],"various":[44],"sources":[45],"biomedical":[47,51],"textbased":[48],"information,":[49],"including":[50],"literature":[52],"social":[54],"media.":[55],"We":[56,80],"formulate":[57],"the":[58,67,78,82],"problem":[59],"binary":[62],"classification":[63],"task":[64],"compare":[66],"performance":[68],"four":[70,88],"state-of-the-art":[71],"attention-based":[72],"neural":[73],"networks":[74],"terms":[76],"F-measure.":[79],"show":[81],"effectiveness":[83],"these":[85],"methods":[86],"different":[89],"benchmarks.":[90]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
