{"id":"https://openalex.org/W7126428470","doi":"https://doi.org/10.18653/v1/2024.findings-eacl.149","title":"CReSE: Benchmark Data and Automatic Evaluation Framework for Recommending Eligibility Criteria from Clinical Trial Information","display_name":"CReSE: Benchmark Data and Automatic Evaluation Framework for Recommending Eligibility Criteria from Clinical Trial Information","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W7126428470","doi":"https://doi.org/10.18653/v1/2024.findings-eacl.149"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2024.findings-eacl.149","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-eacl.149","pdf_url":"https://aclanthology.org/2024.findings-eacl.149.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":"Findings of the Association for Computational Linguistics: EACL 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2024.findings-eacl.149.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080065684","display_name":"Siun Kim","orcid":"https://orcid.org/0000-0003-1090-3978"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","KR"],"is_corresponding":false,"raw_author_name":"Siun Kim","raw_affiliation_strings":["Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025227493","display_name":"Jung\u2010Hyun Won","orcid":"https://orcid.org/0000-0001-7335-8087"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","KR"],"is_corresponding":false,"raw_author_name":"Jung-Hyun Won","raw_affiliation_strings":["Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124601028","display_name":"David R. Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030131487","display_name":"Renqian Luo","orcid":"https://orcid.org/0000-0002-9062-3484"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","KR"],"is_corresponding":false,"raw_author_name":"Renqian Luo","raw_affiliation_strings":["Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124576514","display_name":"Lijun Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","KR"],"is_corresponding":false,"raw_author_name":"Lijun Wu","raw_affiliation_strings":["Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071756681","display_name":"Tao Qin","orcid":"https://orcid.org/0000-0003-0533-0036"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","KR"],"is_corresponding":false,"raw_author_name":"Tao Qin","raw_affiliation_strings":["Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061392624","display_name":"Howard Lee","orcid":"https://orcid.org/0000-0001-6713-5418"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","KR"],"is_corresponding":false,"raw_author_name":"Howard Lee","raw_affiliation_strings":["Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University Seoul National University Seoul National University Microsoft Research Microsoft Research Microsoft Research Seoul National University","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57288224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2243","last_page":"2273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.33489999175071716,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.33489999175071716,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.12600000202655792,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.08749999850988388,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5504999756813049},{"id":"https://openalex.org/keywords/clinical-trial","display_name":"Clinical trial","score":0.5472999811172485},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.2865999937057495},{"id":"https://openalex.org/keywords/information-system","display_name":"Information system","score":0.2816999852657318},{"id":"https://openalex.org/keywords/medline","display_name":"MEDLINE","score":0.2791999876499176}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5575000047683716},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5504999756813049},{"id":"https://openalex.org/C535046627","wikidata":"https://www.wikidata.org/wiki/Q30612","display_name":"Clinical trial","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48660001158714294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30869999527931213},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29440000653266907},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2024.findings-eacl.149","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-eacl.149","pdf_url":"https://aclanthology.org/2024.findings-eacl.149.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":"Findings of the Association for Computational Linguistics: EACL 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2024.findings-eacl.149","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-eacl.149","pdf_url":"https://aclanthology.org/2024.findings-eacl.149.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":"Findings of the Association for Computational Linguistics: EACL 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3385096824","display_name":null,"funder_award_id":"5120200513755","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G4700831490","display_name":null,"funder_award_id":"2022-","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G698754487","display_name":null,"funder_award_id":"5120200513755","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G7776309008","display_name":null,"funder_award_id":"BK21FOUR","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7126428470.pdf","grobid_xml":"https://content.openalex.org/works/W7126428470.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Eligibility":[0],"criteria":[1],"(EC)":[2],"refer":[3],"to":[4,13,27,84,183],"a":[5,16,64,137],"set":[6],"of":[7,67,89,188,195],"conditions":[8],"an":[9,80],"individual":[10],"must":[11],"meet":[12],"participate":[14],"in":[15,30,131,193],"clinical":[17,31,72,87,148,196],"trial,":[18],"defining":[19],"the":[20,86,90,128,177,184,189],"study":[21],"population":[22],"and":[23,43,78,101,103,113,163,186],"minimizing":[24],"potential":[25],"risks":[26],"patients.Previous":[28],"research":[29],"trial":[32,73,76],"design":[33],"has":[34],"been":[35],"primarily":[36],"focused":[37],"on":[38,71,127,151,166,176],"searching":[39],"for":[40],"similar":[41],"trials":[42,149],"generating":[44],"EC":[45,69,91,109,132,153,190],"within":[46],"manual":[47],"instructions,":[48],"employing":[49],"similarity-based":[50],"performance":[51,158],"metrics,":[52,159],"which":[53],"may":[54],"not":[55],"fully":[56],"reflect":[57],"human":[58],"judgment.In":[59],"this":[60],"study,":[61],"we":[62,134],"propose":[63],"novel":[65],"task":[66],"recommending":[68],"based":[70],"information,":[74],"including":[75],"titles,":[77],"introduce":[79],"automatic":[81],"evaluation":[82,168,173],"framework":[83,174],"assess":[85],"validity":[88],"recommendation":[92,154,191],"model.Our":[93],"new":[94],"approach,":[95],"known":[96],"as":[97],"CReSE":[98,120,178],"(Contrastive":[99],"learning":[100,112],"Rephrasing-based":[102],"Clinical":[104],"Relevance-preserving":[105],"Sentence":[106],"Embedding),":[107],"represents":[108],"through":[110],"contrastive":[111],"rephrasing":[114],"via":[115],"large":[116],"language":[117,124],"models":[118,125,155,192],"(LLMs).The":[119],"model":[121,179],"outperforms":[122],"existing":[123],"pre-trained":[126],"biomedical":[129],"domain":[130],"clustering.Additionally,":[133],"have":[135],"curated":[136],"benchmark":[138],"dataset":[139],"comprising":[140],"3.2M":[141],"high-quality":[142],"EC-title":[143],"pairs":[144],"extracted":[145],"from":[146],"270K":[147],"available":[150],"ClinicalTrials.gov.The":[152],"achieve":[156],"commendable":[157],"with":[160],"49.0%":[161],"precision@1":[162],"44.2%":[164],"MAP@5":[165],"our":[167,172],"framework.We":[169],"expect":[170],"that":[171],"built":[175],"will":[180],"contribute":[181],"significantly":[182],"development":[185],"assessment":[187],"terms":[194],"validity.":[197]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-02T00:00:00"}