{"id":"https://openalex.org/W4400529473","doi":"https://doi.org/10.1145/3626772.3661366","title":"Clinical Trial Retrieval via Multi-grained Similarity Learning","display_name":"Clinical Trial Retrieval via Multi-grained Similarity Learning","publication_year":2024,"publication_date":"2024-07-10","ids":{"openalex":"https://openalex.org/W4400529473","doi":"https://doi.org/10.1145/3626772.3661366"},"language":"en","primary_location":{"id":"doi:10.1145/3626772.3661366","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3626772.3661366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarsphere.psu.edu/resources/578fc7ec-5e28-4519-8155-92063fdc2b98/downloads/42900","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052855248","display_name":"Junyu Luo","orcid":"https://orcid.org/0000-0002-4897-7051"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junyu Luo","raw_affiliation_strings":["The Pennsylvania State University, University Park, USA"],"raw_orcid":"https://orcid.org/0000-0002-4897-7051","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100769510","display_name":"Cheng Qian","orcid":"https://orcid.org/0000-0003-2249-4681"},"institutions":[{"id":"https://openalex.org/I4210108991","display_name":"IQVIA (United States)","ror":"https://ror.org/01mk44223","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108991"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cheng Qian","raw_affiliation_strings":["IQVIA, Chicago, USA"],"raw_orcid":"https://orcid.org/0000-0003-2249-4681","affiliations":[{"raw_affiliation_string":"IQVIA, Chicago, USA","institution_ids":["https://openalex.org/I4210108991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030103228","display_name":"Lucas M. Glass","orcid":"https://orcid.org/0000-0001-6613-5205"},"institutions":[{"id":"https://openalex.org/I4210108991","display_name":"IQVIA (United States)","ror":"https://ror.org/01mk44223","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108991"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lucas Glass","raw_affiliation_strings":["IQVIA, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6613-5205","affiliations":[{"raw_affiliation_string":"IQVIA, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I4210108991"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001030192","display_name":"Fenglong Ma","orcid":"https://orcid.org/0000-0002-4999-0303"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fenglong Ma","raw_affiliation_strings":["The Pennsylvania State University, University Park, USA"],"raw_orcid":"https://orcid.org/0000-0002-4999-0303","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2950","last_page":"2954"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9987000226974487,"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"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9934999942779541,"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/T10028","display_name":"Topic Modeling","score":0.9848999977111816,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.73179030418396},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6158812046051025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5060927271842957},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4138810336589813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73179030418396},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6158812046051025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5060927271842957},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4138810336589813},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3626772.3661366","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3626772.3661366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarsphere.psu.edu:d2a4e2d6-7bca-4848-b126-b18dc4de27ca","is_oa":true,"landing_page_url":"https://scholarsphere.psu.edu/resources/d2a4e2d6-7bca-4848-b126-b18dc4de27ca","pdf_url":"https://scholarsphere.psu.edu/resources/578fc7ec-5e28-4519-8155-92063fdc2b98/downloads/42900","source":{"id":"https://openalex.org/S4306401507","display_name":"ScholarSphere (Penn State Libraries)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3130638595","host_organization_name":"Pangasinan State University","host_organization_lineage":["https://openalex.org/I3130638595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:scholarsphere.psu.edu:d2a4e2d6-7bca-4848-b126-b18dc4de27ca","is_oa":true,"landing_page_url":"https://scholarsphere.psu.edu/resources/d2a4e2d6-7bca-4848-b126-b18dc4de27ca","pdf_url":"https://scholarsphere.psu.edu/resources/578fc7ec-5e28-4519-8155-92063fdc2b98/downloads/42900","source":{"id":"https://openalex.org/S4306401507","display_name":"ScholarSphere (Penn State Libraries)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3130638595","host_organization_name":"Pangasinan State University","host_organization_lineage":["https://openalex.org/I3130638595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400529473.pdf","grobid_xml":"https://content.openalex.org/works/W4400529473.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W749188084","https://openalex.org/W2092025391","https://openalex.org/W2114847203","https://openalex.org/W2143331230","https://openalex.org/W2604410201","https://openalex.org/W2795274513","https://openalex.org/W2909678312","https://openalex.org/W2911661483","https://openalex.org/W2940927814","https://openalex.org/W2945127593","https://openalex.org/W2986030491","https://openalex.org/W3012592703","https://openalex.org/W3021397474","https://openalex.org/W3080098168","https://openalex.org/W3087702898","https://openalex.org/W3099085316","https://openalex.org/W3099446234","https://openalex.org/W3102286003","https://openalex.org/W3145630588","https://openalex.org/W3153184434","https://openalex.org/W3155343020","https://openalex.org/W3156413894","https://openalex.org/W3172119680","https://openalex.org/W3175001161","https://openalex.org/W4212862312","https://openalex.org/W4213354024","https://openalex.org/W4285113563","https://openalex.org/W4387848740","https://openalex.org/W4387849020"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Clinical":[0],"trial":[1,43,52,90,115,119],"analysis":[2],"is":[3,19,36,62],"one":[4,20],"of":[5,21,63,97,100],"the":[6,22,113,117,121,126,137,143,174],"main":[7],"business":[8],"directions":[9],"and":[10,14,38,54,116,159,178],"services":[11],"in":[12],"IQVIA,":[13],"reviewing":[15],"past":[16],"similar":[17,74],"studies":[18,75],"most":[23],"critical":[24],"steps":[25],"before":[26],"starting":[27],"a":[28,41,87,131,164],"commercial":[29],"clinical":[30,42,51],"trial.":[31],"The":[32,104],"current":[33],"review":[34,56],"process":[35],"manual":[37],"time-consuming,":[39],"requiring":[40],"analyst":[44],"to":[45,66,72,111,141],"manually":[46],"search":[47],"through":[48],"an":[49,68,148],"extensive":[50],"database":[53],"then":[55],"all":[57],"candidate":[58,118],"studies.":[59],"Therefore,":[60],"it":[61],"great":[64],"interest":[65],"develop":[67],"automatic":[69],"retrieval":[70],"algorithm":[71],"select":[73],"by":[76],"giving":[77],"new":[78],"study":[79],"information.":[80,146],"To":[81,154],"achieve":[82],"this":[83],"goal,":[84],"we":[85,162],"propose":[86],"novel":[88],"group-based":[89],"similarity":[91,101,107,133,145],"learning":[92,102,108,134],"network":[93],"named":[94],"GTSLNet,":[95],"consisting":[96],"two":[98],"kinds":[99],"modules.":[103],"pair-wise":[105],"section-level":[106],"module":[109,135,150],"aims":[110],"compare":[112],"query":[114],"from":[120],"abstract":[122],"semantic":[123],"level":[124],"via":[125],"proposed":[127,175],"section":[128],"transformer.":[129],"Meanwhile,":[130],"word-level":[132],"uses":[136],"word":[138],"similarly":[139],"matrix":[140],"capture":[142],"low-level":[144],"Additionally,":[147],"aggregation":[149],"combines":[151],"these":[152],"similarities.":[153],"address":[155],"potential":[156],"false":[157],"negatives":[158],"noisy":[160],"data,":[161],"introduce":[163],"variance-regularized":[165],"group":[166],"distance":[167],"loss":[168],"function.":[169],"Experiment":[170],"results":[171],"show":[172],"that":[173],"GTSLNet":[176],"significantly":[177],"consistently":[179],"outperforms":[180],"state-of-the-art":[181],"baselines.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
