{"id":"https://openalex.org/W4409014841","doi":"https://doi.org/10.1109/tbdata.2025.3556639","title":"Split Learning on Segmented Healthcare Data","display_name":"Split Learning on Segmented Healthcare Data","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4409014841","doi":"https://doi.org/10.1109/tbdata.2025.3556639"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2025.3556639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2025.3556639","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-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":"https://openalex.org/A5101809782","display_name":"Ling Hu","orcid":"https://orcid.org/0009-0004-4191-0630"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ling Hu","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044528861","display_name":"Tongqing Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongqing Zhou","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067950473","display_name":"Zhihuang Liu","orcid":"https://orcid.org/0000-0001-7583-5086"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihuang Liu","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453028","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0001-8753-3878"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["School of Design, Hunan University, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"School of Design, Hunan University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006334685","display_name":"Zhiping Cai","orcid":"https://orcid.org/0000-0001-5726-833X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiping Cai","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101809782"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":4.7137,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.93983951,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"11","issue":"5","first_page":"2749","last_page":"2763"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.7235999703407288,"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":0.7235999703407288,"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/T10057","display_name":"Face and Expression Recognition","score":0.6753000020980835,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.6338000297546387,"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":0.753386914730072},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5989828705787659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3603048324584961},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3276674747467041}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753386914730072},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5989828705787659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3603048324584961},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3276674747467041},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2025.3556639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2025.3556639","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1532720608","display_name":null,"funder_award_id":"62472434","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5425828656","display_name":null,"funder_award_id":"62102425","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6763376774","display_name":null,"funder_award_id":"62172155","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1557868429","https://openalex.org/W2107862175","https://openalex.org/W2802668759","https://openalex.org/W2809396336","https://openalex.org/W2891233888","https://openalex.org/W2891400669","https://openalex.org/W2914683543","https://openalex.org/W2985862567","https://openalex.org/W2998409174","https://openalex.org/W3002850170","https://openalex.org/W3080098168","https://openalex.org/W3080626793","https://openalex.org/W3091884625","https://openalex.org/W3094433718","https://openalex.org/W3102626224","https://openalex.org/W3168130740","https://openalex.org/W4210683768","https://openalex.org/W4220924718","https://openalex.org/W4380839235","https://openalex.org/W4382318866","https://openalex.org/W4385768065","https://openalex.org/W4385819926","https://openalex.org/W4386707689","https://openalex.org/W4388820050","https://openalex.org/W4390904993","https://openalex.org/W4400070766","https://openalex.org/W4402811098"],"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":{"Sequential":[0],"data":[1,22,53,174],"learning":[2,25,30,34,84,135,150],"is":[3,87,141,158],"vital":[4],"to":[5,68],"harnessing":[6],"the":[7,45,70,94,128,163],"encompassed":[8],"rich":[9],"knowledge":[10],"for":[11,44],"diverse":[12],"downstream":[13],"tasks,":[14],"particularly":[15],"in":[16,64,96,196],"healthcare":[17],"(e.g.,":[18],"disease":[19],"prediction).":[20],"Considering":[21,98],"sensitiveness,":[23],"privacy-preserving":[24,108],"methods,":[26],"based":[27,111],"on":[28,93,112,136,148,171],"federated":[29],"(FL)":[31],"and":[32,62,152,154,182,190],"split":[33,134],"(SL),":[35],"have":[36,101],"been":[37],"widely":[38],"investigated.":[39],"Yet,":[40],"this":[41,79],"work":[42],"identifies,":[43],"first":[46,106],"time,":[47],"existing":[48],"methods":[49],"overlook":[50],"that":[51,99],"sequential":[52,71],"are":[54],"generated":[55],"by":[56,89],"different":[57,60,65,74,102],"patients":[58,100,122],"at":[59],"times":[61],"stored":[63],"hospitals,":[66],"failing":[67],"learn":[69],"correlations":[72],"between":[73],"temporal":[75],"segments.":[76],"To":[77],"fill":[78],"void,":[80],"a":[81,91,113,155],"novel":[82],"distributed":[83],"framework":[85],"<monospace>STSL</monospace>":[86,105],"proposed":[88],"training":[90,130],"model":[92],"segments":[95],"order.":[97],"visit":[103,109,125],"sequences,":[104],"implements":[107],"ordering":[110],"secure":[114],"multi-party":[115],"computation":[116],"mechanism.":[117],"Then":[118],"batch":[119],"scheduling":[120,139],"participates":[121],"with":[123,180],"similar":[124],"(sub-)sequences":[126],"into":[127],"same":[129],"batch,":[131],"facilitating":[132],"subsequent":[133],"batches.":[137],"The":[138],"process":[140],"formulated":[142],"as":[143],"an":[144],"NP-hard":[145],"optimization":[146],"problem":[147],"balancing":[149],"loss":[151],"efficiency":[153],"greedy-based":[156],"solution":[157],"presented.":[159],"Theoretical":[160],"analysis":[161],"proves":[162],"privacy":[164],"preservation":[165],"property":[166],"of":[167],"<monospace>STSL</monospace>.":[168],"Experimental":[169],"results":[170],"real-world":[172],"eICU":[173],"show":[175],"its":[176],"superior":[177],"performance":[178],"compared":[179],"FL":[181],"SL":[183],"(<inline-formula><tex-math":[184],"notation=\"LaTeX\">$5\\%":[185],"\\sim":[186],"28\\%$</tex-math></inline-formula>":[187],"better":[188],"accuracy)":[189],"effectiveness":[191],"(a":[192],"remarkable":[193],"75%":[194],"reduction":[195],"communication":[197],"costs).":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}