{"id":"https://openalex.org/W7150947464","doi":"https://doi.org/10.48550/arxiv.2604.02678","title":"Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis","display_name":"Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7150947464","doi":"https://doi.org/10.48550/arxiv.2604.02678"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02678","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02678","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.02678","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133018489","display_name":"Yao Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133033298","display_name":"Zhiyue Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhiyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056825063","display_name":"Yanxun Xu","orcid":"https://orcid.org/0000-0001-5554-8637"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Yanxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.7580999732017517,"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"}},"topics":[{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.7580999732017517,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.057999998331069946,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"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":0.04540000110864639,"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/weighting","display_name":"Weighting","score":0.7558000087738037},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6186000108718872},{"id":"https://openalex.org/keywords/clinical-trial","display_name":"Clinical trial","score":0.5511000156402588},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4975999891757965},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.439300000667572},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.40290001034736633},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.3617999851703644},{"id":"https://openalex.org/keywords/statistical-power","display_name":"Statistical power","score":0.3043000102043152}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7558000087738037},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6186000108718872},{"id":"https://openalex.org/C535046627","wikidata":"https://www.wikidata.org/wiki/Q30612","display_name":"Clinical trial","level":2,"score":0.5511000156402588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5490000247955322},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.439300000667572},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43720000982284546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4147000014781952},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.40290001034736633},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39329999685287476},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3463999927043915},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C2778648169","wikidata":"https://www.wikidata.org/wiki/Q967768","display_name":"Compatibility (geochemistry)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02678","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02678","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.02678","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02678","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Clinical":[0],"evidence":[1,33,218],"synthesis":[2,219],"requires":[3],"identifying":[4],"relevant":[5,156],"trials":[6,152],"from":[7,92,99,182],"large":[8],"registries":[9],"and":[10,72,102,115,129,139,214],"aggregating":[11],"results":[12],"that":[13,57],"account":[14],"for":[15,217],"population":[16,135],"differences.":[17],"While":[18],"recent":[19],"LLM-based":[20,90],"approaches":[21],"have":[22],"automated":[23,59,205],"components":[24],"of":[25,106,199],"systematic":[26],"review,":[27],"they":[28],"do":[29],"not":[30],"support":[31],"end-to-end":[32],"synthesis.":[34],"Moreover,":[35],"conventional":[36,188],"meta-analysis":[37,171],"weights":[38,133],"studies":[39,157],"by":[40],"statistical":[41,116],"precision":[42,221],"without":[43],"considering":[44],"clinical":[45],"compatibility":[46],"reflected":[47],"in":[48,220],"eligibility":[49,74,127,201],"criteria.":[50],"We":[51],"propose":[52],"EligMeta,":[53],"an":[54,167],"agentic":[55],"framework":[56,125,216],"integrates":[58],"trial":[60,70,107,206],"discovery":[61,207],"with":[62,208],"eligibility-aware":[63,175,209],"meta-analysis,":[64,210],"translating":[65],"natural-language":[66,100],"queries":[67,101],"into":[68,76],"reproducible":[69,215],"selection":[71],"incorporating":[73,200],"alignment":[75,136],"study":[77,132],"weighting":[78,176],"to":[79,121,153,191],"produce":[80],"cohort-specific":[81],"pooled":[82,179],"estimates.":[83],"EligMeta":[84,148,203],"employs":[85],"a":[86,143,212],"hybrid":[87],"architecture":[88],"separating":[89],"reasoning":[91],"deterministic":[93],"execution:":[94],"LLMs":[95],"generate":[96],"interpretable":[97],"rules":[98],"perform":[103],"schema-constrained":[104],"parsing":[105],"metadata,":[108],"while":[109],"all":[110,162],"logical":[111],"operations,":[112],"weight":[113],"computations,":[114],"pooling":[117],"are":[118],"executed":[119],"deterministically":[120],"ensure":[122],"reproducibility.":[123],"The":[124],"structures":[126],"criteria":[128],"computes":[130],"similarity-based":[131],"reflecting":[134],"between":[137],"target":[138],"comparator":[140],"trials.":[141,165],"In":[142,166],"gastric":[144],"cancer":[145],"landscape":[146],"analysis,":[147],"reduced":[149],"4,044":[150],"candidate":[151],"39":[154],"clinically":[155],"through":[158],"rule-based":[159],"filtering,":[160],"recovering":[161],"13":[163],"guideline-cited":[164],"olaparib":[168],"adverse":[169],"events":[170],"across":[172],"four":[173],"trials,":[174],"shifted":[177],"the":[178],"risk":[180],"ratio":[181],"2.18":[183],"(95%":[184,193],"CI:":[185,194],"1.71-2.79)":[186],"under":[187],"Mantel-Haenszel":[189],"estimation":[190],"1.97":[192],"1.76-2.20),":[195],"demonstrating":[196],"quantifiable":[197],"impact":[198],"alignment.":[202],"bridges":[204],"providing":[211],"scalable":[213],"medicine.":[222]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-07T00:00:00"}