{"id":"https://openalex.org/W4412568371","doi":"https://doi.org/10.1109/ichi64645.2025.00016","title":"Examining Imbalance Effects on Performance and Demographic Fairness of Clinical Language Models","display_name":"Examining Imbalance Effects on Performance and Demographic Fairness of Clinical Language Models","publication_year":2025,"publication_date":"2025-06-18","ids":{"openalex":"https://openalex.org/W4412568371","doi":"https://doi.org/10.1109/ichi64645.2025.00016"},"language":"en","primary_location":{"id":"doi:10.1109/ichi64645.2025.00016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ichi64645.2025.00016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 13th International Conference on Healthcare Informatics (ICHI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Precious Jones","orcid":null},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Precious Jones","raw_affiliation_strings":["University of Memphis,Department of Computer Science,Memphis,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Memphis,Department of Computer Science,Memphis,United States","institution_ids":["https://openalex.org/I94658018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063635932","display_name":"Weisi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weisi Liu","raw_affiliation_strings":["University of Memphis,Department of Computer Science,Memphis,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Memphis,Department of Computer Science,Memphis,United States","institution_ids":["https://openalex.org/I94658018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051828530","display_name":"I\u2010Chan Huang","orcid":"https://orcid.org/0000-0002-1194-3923"},"institutions":[{"id":"https://openalex.org/I1313298211","display_name":"St. Jude Children's Research Hospital","ror":"https://ror.org/02r3e0967","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1313298211","https://openalex.org/I2802152183"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"I-Chan Huang","raw_affiliation_strings":["St Jude Children&#x2019;s Research Hospital,Department of Epidemiology and Cancer Control,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"St Jude Children&#x2019;s Research Hospital,Department of Epidemiology and Cancer Control,United States","institution_ids":["https://openalex.org/I1313298211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027237221","display_name":"Xiaolei Huang","orcid":"https://orcid.org/0000-0003-0478-8715"},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolei Huang","raw_affiliation_strings":["University of Memphis,Department of Computer Science,Memphis,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Memphis,Department of Computer Science,Memphis,United States","institution_ids":["https://openalex.org/I94658018"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8863,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79427605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"58","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.6470999717712402,"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"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.6470999717712402,"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/T10028","display_name":"Topic Modeling","score":0.5619000196456909,"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/T10350","display_name":"Electronic Health Records Systems","score":0.5410000085830688,"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/computer-science","display_name":"Computer science","score":0.602823793888092},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3595580458641052},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.14169913530349731}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.602823793888092},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3595580458641052},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14169913530349731}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ichi64645.2025.00016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ichi64645.2025.00016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 13th International Conference on Healthcare Informatics (ICHI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1995365999","https://openalex.org/W2116456152","https://openalex.org/W2791170418","https://openalex.org/W2987216115","https://openalex.org/W3086140553","https://openalex.org/W3209254806","https://openalex.org/W3216092102","https://openalex.org/W4207057807","https://openalex.org/W4283785590","https://openalex.org/W4310568840","https://openalex.org/W4310942459","https://openalex.org/W4313439128","https://openalex.org/W4385848286","https://openalex.org/W4386757283","https://openalex.org/W4391094998","https://openalex.org/W4392781760","https://openalex.org/W4396736209","https://openalex.org/W4401043650","https://openalex.org/W4401753960","https://openalex.org/W4402916511","https://openalex.org/W4404783689","https://openalex.org/W6755754581","https://openalex.org/W6761260114","https://openalex.org/W6769243733","https://openalex.org/W6781892109","https://openalex.org/W6797134598","https://openalex.org/W6810368914","https://openalex.org/W6810598201","https://openalex.org/W6841980587","https://openalex.org/W6846643419","https://openalex.org/W6851413434","https://openalex.org/W6854926761","https://openalex.org/W6871851305","https://openalex.org/W6873366139","https://openalex.org/W6874530507","https://openalex.org/W6929320213"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Data":[0],"imbalance":[1,44,65,109,121],"is":[2],"a":[3,77,137],"fundamental":[4],"challenge":[5],"in":[6,14,34,69,76,156],"applying":[7],"language":[8,28,93,154],"models":[9,29,155],"to":[10,131],"biomedical":[11,35,92],"applications,":[12],"particularly":[13],"ICD":[15,70],"code":[16,71],"prediction":[17],"tasks":[18],"where":[19],"label":[20],"and":[21,48,66,85,100,113,126,152],"demographic":[22,51,114],"distributions":[23],"are":[24],"uneven.":[25],"While":[26],"state-of-the-art":[27,91],"have":[30,39],"been":[31],"increasingly":[32],"adopted":[33],"tasks,":[36],"few":[37],"studies":[38],"systematically":[40],"examined":[41],"how":[42],"data":[43,64,80,108,120],"affects":[45],"model":[46,67,124],"performance":[47,68,98,111,125],"fairness":[49],"across":[50,81],"groups.":[52],"This":[53],"study":[54,117,144],"fills":[55],"the":[56,61,105,132],"gap":[57],"by":[58,90],"statistically":[59],"probing":[60],"relationship":[62],"between":[63],"prediction.":[72],"We":[73,141],"analyze":[74],"imbalances":[75],"standard":[78],"benchmark":[79],"gender,":[82],"age,":[83],"ethnicity,":[84],"social":[86],"determinants":[87],"of":[88,107],"health":[89],"models.":[94],"By":[95],"deploying":[96],"diverse":[97],"metrics":[99],"statistical":[101],"analyses,":[102],"we":[103],"explore":[104],"influence":[106],"on":[110],"variations":[112],"fairness.":[115],"Our":[116],"shows":[118],"that":[119],"significantly":[122],"impacts":[123],"fairness,":[127],"but":[128],"feature":[129],"similarity":[130],"majority":[133],"class":[134],"may":[135],"be":[136],"more":[138,150],"critical":[139],"factor.":[140],"believe":[142],"this":[143],"provides":[145],"valuable":[146],"insights":[147],"for":[148],"developing":[149],"equitable":[151],"robust":[153],"healthcare":[157],"applications<sup":[158],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[159],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
