{"id":"https://openalex.org/W4301242115","doi":"https://doi.org/10.1109/icc45855.2022.9839100","title":"Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health","display_name":"Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4301242115","doi":"https://doi.org/10.1109/icc45855.2022.9839100"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9839100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839100","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","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":"https://openalex.org/A5001459619","display_name":"Chong Yu","orcid":"https://orcid.org/0000-0002-6244-3486"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chong Yu","raw_affiliation_strings":["University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,USA","Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,USA","institution_ids":["https://openalex.org/I114395901"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, USA","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017959427","display_name":"Shuaiqi Shen","orcid":"https://orcid.org/0000-0003-4706-5330"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuaiqi Shen","raw_affiliation_strings":["University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,USA","Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,USA","institution_ids":["https://openalex.org/I114395901"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, USA","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443968","display_name":"Shiqiang Wang","orcid":"https://orcid.org/0000-0003-2090-5512"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shiqiang Wang","raw_affiliation_strings":["IBM T. J. Watson Research Center,New York,USA","IBM T. J. Watson Research Center, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T. J. Watson Research Center,New York,USA","institution_ids":[]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, New York, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736887","display_name":"Kuan Zhang","orcid":"https://orcid.org/0000-0002-4262-153X"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuan Zhang","raw_affiliation_strings":["University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,USA","Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,USA","institution_ids":["https://openalex.org/I114395901"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, USA","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100457332","display_name":"Hai Zhao","orcid":"https://orcid.org/0000-0002-3392-2584"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Zhao","raw_affiliation_strings":["Northeastern University,Department of Computer Science and Engineering,Shenyang,China","Department of Computer Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Department of Computer Science and Engineering,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9343,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.76851312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1263","last_page":"1268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9952999949455261,"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/T10237","display_name":"Cryptography and Data Security","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.7635438442230225},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7617682218551636},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.6184395551681519},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5511721968650818},{"id":"https://openalex.org/keywords/descent","display_name":"Descent (aeronautics)","score":0.4283342957496643},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.365581214427948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3455938696861267},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.0896998941898346}],"concepts":[{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.7635438442230225},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7617682218551636},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.6184395551681519},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5511721968650818},{"id":"https://openalex.org/C2776637919","wikidata":"https://www.wikidata.org/wiki/Q624380","display_name":"Descent (aeronautics)","level":2,"score":0.4283342957496643},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.365581214427948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3455938696861267},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0896998941898346},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9839100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839100","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332299","display_name":"National Institute of Food and Agriculture","ror":"https://ror.org/05qx3fv49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2912213068","https://openalex.org/W2944604407","https://openalex.org/W2954070046","https://openalex.org/W2978648093","https://openalex.org/W3041966875","https://openalex.org/W3100779497","https://openalex.org/W3101973032","https://openalex.org/W3111512201","https://openalex.org/W3135231128","https://openalex.org/W3156220053","https://openalex.org/W3190471748","https://openalex.org/W4210656975","https://openalex.org/W4287022937","https://openalex.org/W4294106961","https://openalex.org/W4318619660","https://openalex.org/W6728757088","https://openalex.org/W6768844495","https://openalex.org/W6771536673","https://openalex.org/W6781119572","https://openalex.org/W6785528530","https://openalex.org/W6800453881"],"related_works":["https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668","https://openalex.org/W2015288657","https://openalex.org/W3008318776","https://openalex.org/W1977633006","https://openalex.org/W2041416246"],"abstract_inverted_index":{"E-health":[0],"systems":[1],"consist":[2],"of":[3,113,124,197,214,226],"intelligent":[4],"devices,":[5],"medical":[6,91],"institutions,":[7],"edge":[8,187],"nodes,":[9],"and":[10,18,32,106,128,152,249],"cloud":[11],"servers":[12],"to":[13,126,144,169,202,210],"improve":[14,176],"healthcare":[15],"service":[16],"quality":[17],"efficiency.":[19],"In":[20,117],"e-health":[21,97,134],"systems,":[22],"patients\u2019":[23],"data":[24,43,71,147,204],"are":[25,53,149,184],"cooperatively":[26],"collected":[27],"by":[28,182],"their":[29],"wearable":[30,45],"devices":[31,46,183],"the":[33,48,122,166,171,212,218,224,227,238,244],"hospital":[34],"they":[35],"have":[36],"visited,":[37],"i.e.,":[38,58,73],"vertically":[39],"distributed":[40,75],"data.":[41,61,76,92,135],"The":[42,195,234],"on":[44,90,133,186,217],"share":[47],"same":[49],"feature":[50],"set":[51],"but":[52],"different":[54],"in":[55,69,96],"sample":[56],"spaces,":[57],"horizontally":[59],"partitioned":[60],"Meanwhile,":[62],"hospitals":[63],"target":[64],"various":[65],"user":[66],"groups":[67],"resulting":[68],"high":[70],"diversity,":[72],"non-identically":[74,153],"These":[77],"three":[78],"characteristics":[79],"cause":[80],"that":[81,148,243],"existing":[82],"federated":[83,141],"learning":[84,115,142],"frameworks":[85],"cannot":[86],"efficiently":[87,127],"train":[88,130],"models":[89,132,180,199,216],"Furthermore,":[93],"model":[94],"training":[95,177],"is":[98,200],"time-sensitive":[99],"because":[100],"some":[101],"diseases":[102],"mutate":[103],"very":[104],"quickly":[105],"spread":[107],"easily,":[108],"which":[109],"requires":[110],"fast":[111,248],"convergence":[112,225],"machine":[114],"algorithms.":[116],"this":[118],"paper,":[119],"we":[120,137,156],"address":[121],"problem":[123],"how":[125],"rapidly":[129],"global":[131,173,208,219],"Specifically,":[136],"propose":[138],"a":[139,158,231],"multilayer":[140],"framework":[143,168],"cope":[145],"with":[146,193],"vertically,":[150],"horizontally,":[151],"distributed.":[154],"Moreover,":[155],"develop":[157],"Multi-Layer":[159],"Stochastic":[160],"Gradient":[161],"Descent":[162],"(MLSGD)":[163],"algorithm":[164,229,246],"towards":[165],"proposed":[167,245],"learn":[170],"optimal":[172],"model.":[174,220],"To":[175],"efficiency,":[178],"partial":[179],"learned":[181],"aggregated":[185],"nodes":[188],"before":[189],"exchanging":[190],"intermediate":[191],"results":[192,236],"hospitals.":[194],"weight":[196],"local":[198,203,215],"proportional":[201],"size":[205],"when":[206],"performing":[207],"aggregation":[209],"balance":[211],"impact":[213],"We":[221],"also":[222],"prove":[223],"MLSGD":[228],"from":[230,237],"theoretical":[232],"perspective.":[233],"experimental":[235],"real-world":[239],"dataset":[240],"MIMIC-III":[241],"validate":[242],"converges":[247],"achieves":[250],"desired":[251],"accuracy.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
