{"id":"https://openalex.org/W7204153935","doi":"https://doi.org/10.1145/3799682.3840734","title":"SynEHR: Joint Modeling Inter-visit Temporal Evolution and Intra-visit Clinical Structure for Longitudinal EHR Synthesis","display_name":"SynEHR: Joint Modeling Inter-visit Temporal Evolution and Intra-visit Clinical Structure for Longitudinal EHR Synthesis","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7204153935","doi":"https://doi.org/10.1145/3799682.3840734"},"language":"en","primary_location":{"id":"doi:10.1145/3799682.3840734","doi":"https://doi.org/10.1145/3799682.3840734","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840734","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3799682.3840734","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133884774","display_name":"Ximiao Li","orcid":"https://orcid.org/0009-0004-2590-4863","observed_orcids":["https://orcid.org/0009-0004-2590-4863"]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ximiao Li","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0009-0004-2590-4863","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144374003","display_name":"Lin Jiang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin Jiang","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0009-0003-5770-3161","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082235101","display_name":"Rongchao Xu","orcid":"https://orcid.org/0000-0002-1542-5162","observed_orcids":["https://orcid.org/0000-0002-1542-5162","https://orcid.org/0009-0006-5226-5715"]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rongchao Xu","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0009-0006-5226-5715","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144375799","display_name":"Dahai Yu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dahai Yu","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0009-0006-5090-9070","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148044168","display_name":"Zhe He","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe He","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0000-0003-3608-0244","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137616449","display_name":"Guang Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guang Wang","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-7739-7945","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67075824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2846","last_page":"2857"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9916999936103821,"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":0.9916999936103821,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.003700000001117587,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10350","display_name":"Electronic Health Records Systems","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-electronic-health-records","display_name":"synthetic electronic health records","score":0.8690000176429749},{"id":"https://openalex.org/keywords/relational-representation","display_name":"relational representation","score":0.6510000228881836},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.7369999885559082},{"id":"https://openalex.org/keywords/data-privacy","display_name":"data privacy","score":0.5490000247955322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6757000088691711},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5616000294685364},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5180000066757202},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4772999882698059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47620001435279846},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.397599995136261},{"id":"https://openalex.org/C3020672099","wikidata":"https://www.wikidata.org/wiki/Q857354","display_name":"Longitudinal data","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.37070000171661377},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3601999878883362},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.31139999628067017},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.2957000136375427},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C2987896495","wikidata":"https://www.wikidata.org/wiki/Q5416716","display_name":"Event data","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25999999046325684}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3799682.3840734","doi":"https://doi.org/10.1145/3799682.3840734","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840734","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.21673","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.21673","pdf_url":"https://arxiv.org/pdf/2608.21673","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.21673","doi":"https://doi.org/10.48550/arxiv.2608.21673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.21673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"doi:10.1145/3799682.3840734","doi":"https://doi.org/10.1145/3799682.3840734","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840734","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.4000000059604645,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1801626688","display_name":null,"funder_award_id":"R21HS029969","funder_id":"https://openalex.org/F4320332177","funder_display_name":"Agency for Healthcare Research and Quality"},{"id":"https://openalex.org/G9000865597","display_name":"INSiGHTS - Innovative Next Steps in Gaining Health Improvements Through Translational Science","funder_award_id":"UM1TR005128","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G9000872377","display_name":"Precision HIV Prevention: Piloting a youth learning health community","funder_award_id":"R21MH137736","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"},{"id":"https://openalex.org/G9000912573","display_name":"SHARE Program: Innovations in Translational Behavioral Science to Improve Self-management of HIV and Alcohol Reaching Emerging adults","funder_award_id":"P01AA029547","funder_id":"https://openalex.org/F4320337330","funder_display_name":"National Institute on Alcohol Abuse and Alcoholism"}],"funders":[{"id":"https://openalex.org/F4320316438","display_name":"Georgia Clinical and Translational Science Alliance","ror":"https://ror.org/034hw7m59"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332177","display_name":"Agency for Healthcare Research and Quality","ror":"https://ror.org/03jmfdf59"},{"id":"https://openalex.org/F4320337330","display_name":"National Institute on Alcohol Abuse and Alcoholism","ror":"https://ror.org/02jzrsm59"},{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4414585342","https://openalex.org/W4386324432","https://openalex.org/W3115159903","https://openalex.org/W4393147043","https://openalex.org/W4406457803","https://openalex.org/W4385573654","https://openalex.org/W7168185613","https://openalex.org/W4401864355","https://openalex.org/W4412876887","https://openalex.org/W4205760215"],"abstract_inverted_index":{"Longitudinal":[0],"electronic":[1],"health":[2],"records":[3,67],"(EHRs)":[4],"document":[5],"patients'":[6],"sequences":[7],"of":[8,17,36,56],"clinical":[9,54,94],"visits":[10,141],"over":[11],"time,":[12],"preserving":[13,49],"the":[14,50,174],"temporal":[15,90,138],"evolution":[16,91],"disease":[18],"progression":[19],"and":[20,53,63,92,103,142,179,192,207],"care":[21],"delivery.":[22],"However,":[23],"real":[24,66],"longitudinal":[25,120,210],"EHRs":[26],"are":[27,68,124],"difficult":[28],"to":[29,100,153,172],"access":[30],"because":[31],"they":[32,82],"contain":[33],"large":[34],"amounts":[35],"fine-grained,":[37],"patient-specific":[38,156],"information.":[39],"Synthetic":[40],"EHR":[41,121,187,211],"generation":[42,170],"therefore":[43],"provides":[44],"a":[45,114,131,143,163],"valuable":[46],"approach":[47],"for":[48,119,177],"statistical":[51],"patterns":[52],"structure":[55],"patient":[57,151],"visit":[58,80,106],"trajectories,":[59],"enabling":[60],"broader":[61],"modeling":[62],"analysis":[64],"when":[65],"limited.":[69],"Although":[70],"recent":[71],"generative":[72],"models":[73,201],"have":[74],"made":[75],"progress":[76],"in":[77,85,97,128],"producing":[78],"future":[79],"sequences,":[81],"remain":[83],"limited":[84],"explicitly":[86],"integrating":[87],"inter-visit":[88],"irregular":[89,137],"intra-visit":[93],"event":[95],"structures":[96],"EHRs,":[98],"leading":[99],"clinically":[101,180,205],"inconsistent":[102],"temporally":[104,178,208],"unrealistic":[105],"sequences.":[107],"In":[108],"this":[109],"work,":[110],"we":[111],"propose":[112],"SynEHR,":[113,129],"lightweight":[115],"adaptive":[116],"LLM-based":[117],"framework":[118],"synthesis.":[122],"There":[123],"two":[125,175],"novel":[126],"designs":[127],"i.e.,":[130],"Temporal":[132],"State":[133],"Conditioning":[134],"Module":[135,146],"captures":[136],"states":[139,149],"across":[140,189],"Temporal-Relational":[144],"Adaptation":[145],"combines":[147],"these":[148],"with":[150,168],"history":[152],"dynamically":[154],"construct":[155],"relational":[157],"representations.":[158],"SynEHR":[159,198],"then":[160],"builds":[161],"on":[162,185],"parameter-efficient":[164],"LoRA-adapted":[165],"language-model":[166],"generator":[167],"next-visit":[169],"capability":[171],"train":[173],"modules":[176],"informed":[181],"generation.":[182],"Extensive":[183],"experiments":[184],"real-world":[186],"datasets":[188],"fidelity,":[190],"privacy,":[191],"downstream":[193],"utility":[194],"evaluations":[195],"demonstrate":[196],"that":[197],"outperforms":[199],"state-of-the-art":[200],"by":[202],"generating":[203],"more":[204],"coherent":[206],"faithful":[209],"data.":[212]},"counts_by_year":[],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2026-08-26T00:00:00"}
