{"id":"https://openalex.org/W2970839731","doi":"https://doi.org/10.18653/v1/w19-5038","title":"Extracting relations between outcomes and significance levels in Randomized Controlled Trials (RCTs) publications","display_name":"Extracting relations between outcomes and significance levels in Randomized Controlled Trials (RCTs) publications","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970839731","doi":"https://doi.org/10.18653/v1/w19-5038","mag":"2970839731"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-5038","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5038","pdf_url":"https://www.aclweb.org/anthology/W19-5038.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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-5038.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013379021","display_name":"Anna Koroleva","orcid":"https://orcid.org/0000-0002-7245-6539"},"institutions":[{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404"]},{"id":"https://openalex.org/I4210115485","display_name":"Laboratoire d'Informatique pour la M\u00e9canique et les Sciences de l'Ing\u00e9nieur","ror":"https://ror.org/01raq4x89","country_code":"FR","type":"facility","lineage":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I4210115485","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Anna Koroleva","raw_affiliation_strings":["LIMSI - Laboratoire d'Informatique pour la M\u00e9canique et les Sciences de l'Ing\u00e9nieur (Universit\u00e9 Paris-Sud B\u00e2t. 507 - Rue du Belv\u00e9d\u00e8re -91405 ORSAY CEDEX - France)"],"affiliations":[{"raw_affiliation_string":"LIMSI - Laboratoire d'Informatique pour la M\u00e9canique et les Sciences de l'Ing\u00e9nieur (Universit\u00e9 Paris-Sud B\u00e2t. 507 - Rue du Belv\u00e9d\u00e8re -91405 ORSAY CEDEX - France)","institution_ids":["https://openalex.org/I4210115485","https://openalex.org/I102197404"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047797750","display_name":"Patrick Paroubek","orcid":"https://orcid.org/0000-0002-4302-1894"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patrick Paroubek","raw_affiliation_strings":["STL - Sciences et Technologies des Langues - LISN (France)"],"affiliations":[{"raw_affiliation_string":"STL - Sciences et Technologies des Langues - LISN (France)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013379021"],"corresponding_institution_ids":["https://openalex.org/I102197404","https://openalex.org/I4210115485"],"apc_list":null,"apc_paid":null,"fwci":0.2893,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6673977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"359","last_page":"369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10206","display_name":"Meta-analysis and systematic reviews","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9810000061988831,"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/statistical-significance","display_name":"Statistical significance","score":0.7951774597167969},{"id":"https://openalex.org/keywords/randomized-controlled-trial","display_name":"Randomized controlled trial","score":0.638981819152832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5821744203567505},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.566565215587616},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5311468839645386},{"id":"https://openalex.org/keywords/intervention","display_name":"Intervention (counseling)","score":0.5218747854232788},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.5187704563140869},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5187106728553772},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.5003213882446289},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4732701778411865},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.468749076128006},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4541248679161072},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.43229764699935913},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4243812561035156},{"id":"https://openalex.org/keywords/clinical-significance","display_name":"Clinical significance","score":0.4155479371547699},{"id":"https://openalex.org/keywords/significance-testing","display_name":"Significance testing","score":0.415225088596344},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.41412675380706787},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.41291365027427673},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.33244839310646057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2504323720932007},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24088740348815918},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21713736653327942},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18269377946853638},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07251685857772827}],"concepts":[{"id":"https://openalex.org/C65409693","wikidata":"https://www.wikidata.org/wiki/Q425265","display_name":"Statistical significance","level":2,"score":0.7951774597167969},{"id":"https://openalex.org/C168563851","wikidata":"https://www.wikidata.org/wiki/Q1436668","display_name":"Randomized controlled trial","level":2,"score":0.638981819152832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5821744203567505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.566565215587616},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5311468839645386},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.5218747854232788},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.5187704563140869},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5187106728553772},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.5003213882446289},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4732701778411865},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.468749076128006},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4541248679161072},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.43229764699935913},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4243812561035156},{"id":"https://openalex.org/C63363279","wikidata":"https://www.wikidata.org/wiki/Q5133848","display_name":"Clinical significance","level":2,"score":0.4155479371547699},{"id":"https://openalex.org/C2984474657","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Significance testing","level":2,"score":0.415225088596344},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.41412675380706787},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.41291365027427673},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33244839310646057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2504323720932007},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24088740348815918},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21713736653327942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18269377946853638},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07251685857772827},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/w19-5038","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5038","pdf_url":"https://www.aclweb.org/anthology/W19-5038.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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04449412v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04449412","pdf_url":"https://hal.science/hal-04449412v1/document","source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 18th BioNLP Workshop and Shared Task, Aug 2019, Florence, France. pp.359-369, &#x27E8;10.18653/v1/W19-5038&#x27E9;","raw_type":"Conference papers"},{"id":"pmh:oai:zenodo.org:3608714","is_oa":true,"landing_page_url":"https://zenodo.org/record/3608714","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"doi:10.18653/v1/w19-5038","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5038","pdf_url":"https://www.aclweb.org/anthology/W19-5038.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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.75,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2970839731.pdf","grobid_xml":"https://content.openalex.org/works/W2970839731.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W43033716","https://openalex.org/W85058473","https://openalex.org/W164706946","https://openalex.org/W1502922572","https://openalex.org/W1587157779","https://openalex.org/W1901887568","https://openalex.org/W1985258161","https://openalex.org/W1988790447","https://openalex.org/W1995054545","https://openalex.org/W2014279397","https://openalex.org/W2056132907","https://openalex.org/W2064314529","https://openalex.org/W2070493638","https://openalex.org/W2097352005","https://openalex.org/W2100642133","https://openalex.org/W2101234009","https://openalex.org/W2109146014","https://openalex.org/W2164005910","https://openalex.org/W2210216123","https://openalex.org/W2250539671","https://openalex.org/W2251329024","https://openalex.org/W2299418665","https://openalex.org/W2620579047","https://openalex.org/W2740782465","https://openalex.org/W2741560830","https://openalex.org/W2741988747","https://openalex.org/W2885911173","https://openalex.org/W2896457183","https://openalex.org/W2911489562","https://openalex.org/W2911964244","https://openalex.org/W2922551710","https://openalex.org/W2953384591","https://openalex.org/W2962902328","https://openalex.org/W2963341956","https://openalex.org/W2964167098","https://openalex.org/W2964348125","https://openalex.org/W4239510810","https://openalex.org/W4393441609","https://openalex.org/W4398681938"],"related_works":["https://openalex.org/W2073700667","https://openalex.org/W2573129589","https://openalex.org/W1505970868","https://openalex.org/W3195377381","https://openalex.org/W4318819743","https://openalex.org/W4378232449","https://openalex.org/W2912003489","https://openalex.org/W1573752215","https://openalex.org/W2183556593","https://openalex.org/W2093946342"],"abstract_inverted_index":{"Randomized":[0],"controlled":[1],"trials":[2],"assess":[3],"the":[4,31,37,44,53,68,113],"effects":[5],"of":[6,52,75,101,108],"an":[7,49],"experimental":[8,32],"intervention":[9,16,33],"by":[10,112],"comparing":[11],"it":[12],"to":[13,19,28,36,60],"a":[14,56,73,93,99],"control":[15],"with":[17,78],"regard":[18],"some":[20],"variables":[21],"-trial":[22],"outcomes.Statistical":[23],"hypothesis":[24],"testing":[25],"is":[26,34,40,48],"used":[27],"test":[29],"if":[30],"superior":[35],"control.Statistical":[38],"significance":[39,65],"typically":[41],"reported":[42,63],"for":[43],"measured":[45],"outcomes":[46],"and":[47,67,85,98],"important":[50],"characteristic":[51],"results.We":[54],"propose":[55],"machine":[57],"learning":[58,103],"approach":[59],"automatically":[61],"extract":[62],"outcomes,":[64],"levels":[66],"relation":[69],"between":[70],"them.We":[71],"annotated":[72],"corpus":[74],"663":[76],"sentences":[77],"2,552":[79],"outcomesignificance":[80],"level":[81],"relations":[82],"(1,372":[83],"positive":[84],"1,180":[86],"negative":[87],"relations).We":[88],"compared":[89],"several":[90],"classifiers,":[91],"using":[92],"manually":[94],"crafted":[95],"feature":[96],"set,":[97],"number":[100],"deep":[102],"models.The":[104],"best":[105],"performance":[106],"(F-measure":[107],"94%)":[109],"was":[110],"shown":[111],"BioBERT":[114],"fine-tuned":[115],"model.":[116]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-21T08:13:44.787528","created_date":"2025-10-10T00:00:00"}
