{"id":"https://openalex.org/W7113897916","doi":"https://doi.org/10.1145/3765612.3767246","title":"Developing Fairness-Aware Task Decomposition to Improve Equity in Post-Spinal Fusion Complication Prediction","display_name":"Developing Fairness-Aware Task Decomposition to Improve Equity in Post-Spinal Fusion Complication Prediction","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W7113897916","doi":"https://doi.org/10.1145/3765612.3767246"},"language":null,"primary_location":{"id":"doi:10.1145/3765612.3767246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767246","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3765612.3767246","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yining Yuan","orcid":"https://orcid.org/0009-0000-6157-8605"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yining Yuan","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0009-0000-6157-8605","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":null,"display_name":"J Ben Tamo","orcid":"https://orcid.org/0009-0003-3780-1047"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J Ben Tamo","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0009-0003-3780-1047","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenqi Shi","orcid":"https://orcid.org/0000-0001-8972-7342"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenqi Shi","raw_affiliation_strings":["University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-8972-7342","affiliations":[{"raw_affiliation_string":"University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yishan Zhong","orcid":"https://orcid.org/0000-0002-7010-4521"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yishan Zhong","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7010-4521","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Micky C Nnamdi","orcid":"https://orcid.org/0009-0007-0915-6342"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Micky C Nnamdi","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0009-0007-0915-6342","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":null,"display_name":"B Randall Brenn","orcid":"https://orcid.org/0000-0002-9551-544X"},"institutions":[{"id":"https://openalex.org/I4210129524","display_name":"Shriners Hospitals for Children - Philadelphia","ror":"https://ror.org/036z11b33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210129524","https://openalex.org/I4210144267"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"B Randall Brenn","raw_affiliation_strings":["Shriners Hospitals for Children, Philadelphia, PA, Greece"],"raw_orcid":"https://orcid.org/0000-0002-9551-544X","affiliations":[{"raw_affiliation_string":"Shriners Hospitals for Children, Philadelphia, PA, Greece","institution_ids":["https://openalex.org/I4210129524"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Steven W. Hwang","orcid":"https://orcid.org/0000-0003-0832-3683"},"institutions":[{"id":"https://openalex.org/I4210129524","display_name":"Shriners Hospitals for Children - Philadelphia","ror":"https://ror.org/036z11b33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210129524","https://openalex.org/I4210144267"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven W. Hwang","raw_affiliation_strings":["Shriners Hospitals for Children, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0832-3683","affiliations":[{"raw_affiliation_string":"Shriners Hospitals for Children, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I4210129524"]}]},{"author_position":"last","author":{"id":null,"display_name":"May Dongmei Wang","orcid":"https://orcid.org/0000-0003-3961-3608"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"May Dongmei Wang","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3961-3608","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.62665419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.36149999499320984,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.36149999499320984,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10562","display_name":"Total Knee Arthroplasty Outcomes","score":0.1551000028848648,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10238","display_name":"Spine and Intervertebral Disc Pathology","score":0.09790000319480896,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4634999930858612},{"id":"https://openalex.org/keywords/equity","display_name":"Equity (law)","score":0.44830000400543213},{"id":"https://openalex.org/keywords/odds","display_name":"Odds","score":0.4343000054359436},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.3962000012397766},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.3919999897480011},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.36559998989105225},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.34139999747276306},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.31459999084472656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5335000157356262},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4814000129699707},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4489000141620636},{"id":"https://openalex.org/C199728807","wikidata":"https://www.wikidata.org/wiki/Q2578557","display_name":"Equity (law)","level":2,"score":0.44830000400543213},{"id":"https://openalex.org/C143095724","wikidata":"https://www.wikidata.org/wiki/Q515895","display_name":"Odds","level":3,"score":0.4343000054359436},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.36559998989105225},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31520000100135803},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C156957248","wikidata":"https://www.wikidata.org/wiki/Q1862216","display_name":"Odds ratio","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C3018781618","wikidata":"https://www.wikidata.org/wiki/Q454812","display_name":"Clinical judgement","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2883000075817108},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C81182388","wikidata":"https://www.wikidata.org/wiki/Q353963","display_name":"Complication","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3765612.3767246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767246","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3765612.3767246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767246","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.5202706456184387}],"awards":[],"funders":[{"id":"https://openalex.org/F4320313002","display_name":"Shriners Hospitals for Children","ror":"https://ror.org/03e8tm275"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1978058582","https://openalex.org/W2031707040","https://openalex.org/W2124352049","https://openalex.org/W2126291110","https://openalex.org/W2802683939","https://openalex.org/W2964151070","https://openalex.org/W3023550993","https://openalex.org/W3042276730","https://openalex.org/W3170933632","https://openalex.org/W3181414820","https://openalex.org/W4280505635","https://openalex.org/W4311102276","https://openalex.org/W4323539544","https://openalex.org/W4387807034","https://openalex.org/W4388667118","https://openalex.org/W4399886249","https://openalex.org/W4400320510","https://openalex.org/W4405424272","https://openalex.org/W4406001297","https://openalex.org/W6884825645"],"related_works":[],"abstract_inverted_index":{"Fairness":[0],"in":[1,24],"clinical":[2],"prediction":[3,49],"models":[4],"remains":[5],"an":[6,102],"open":[7],"challenge,":[8],"as":[9,71],"many":[10],"methods":[11],"oversimplify":[12],"outcomes":[13],"and":[14,47,73,89,97,106,124,132,134,146,157,165,182],"inadvertently":[15],"propagate":[16],"demographic":[17,119],"biases.":[18],"This":[19],"issue":[20],"is":[21],"especially":[22],"consequential":[23],"spinal":[25],"fusion":[26],"surgery":[27],"for":[28,45,130,137,186],"scoliosis,":[29],"a":[30,40,81],"high-risk":[31],"procedure":[32],"with":[33],"heterogeneous":[34],"patient":[35,158],"outcomes.":[36],"We":[37],"present":[38],"FAIR-MTL,":[39],"fairness-aware":[41,173],"multitask":[42,83],"learning":[43],"framework":[44],"equitable":[46],"fine-grained":[48],"of":[50,104,108],"postoperative":[51],"complication":[52,112],"severity.":[53],"FAIR-MTL":[54,100],"integrates":[55],"Sensitive":[56],"Set":[57],"Invariance":[58],"(SSI)":[59],"to":[60,67,122,128],"identify":[61],"latent":[62],"subgroups":[63,76],"that":[64,171],"are":[65],"invariant":[66],"sensitive":[68],"attributes,":[69],"such":[70],"age":[72],"gender.":[74],"These":[75],"form":[77],"task-specific":[78],"branches":[79],"within":[80],"shared":[82],"neural":[84],"network,":[85],"enabling":[86],"personalized":[87],"modeling":[88],"subgroup":[90],"adaptivity":[91],"while":[92,115],"jointly":[93],"optimizing":[94],"predictive":[95],"accuracy":[96,107],"fairness":[98,141],"constraints.":[99],"achieves":[101],"AUC":[103],"0.86":[105],"75%":[109],"across":[110],"four":[111],"severity":[113],"classes":[114],"reducing":[116],"the":[117],"average":[118],"parity":[120],"difference":[121,127],"0.055":[123],"equalized":[125],"odds":[126],"0.094":[129],"gender,":[131],"0.056":[133],"0.148,":[135],"respectively":[136],"age,":[138],"substantially":[139],"improving":[140],"over":[142],"standard":[143],"baselines.":[144],"SHAP":[145],"Gini":[147],"importance":[148],"analyses":[149],"highlight":[150],"clinically":[151,183],"relevant":[152],"predictors,":[153],"including":[154],"hematocrit,":[155],"hemoglobin,":[156],"weight,":[159],"providing":[160],"transparency":[161],"at":[162],"both":[163],"global":[164],"individual":[166],"levels.":[167],"Our":[168],"results":[169],"demonstrate":[170],"integrating":[172],"task":[174],"decomposition":[175],"into":[176],"model":[177],"design":[178],"enables":[179],"equitable,":[180],"interpretable,":[181],"actionable":[184],"predictions":[185],"surgical":[187],"risk":[188],"stratification.":[189]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-12-11T00:00:00"}
