{"id":"https://openalex.org/W4387005287","doi":"https://doi.org/10.1109/e-science58273.2023.10254908","title":"Client Recruitment for Federated Learning in ICU Length of Stay Prediction","display_name":"Client Recruitment for Federated Learning in ICU Length of Stay Prediction","publication_year":2023,"publication_date":"2023-09-25","ids":{"openalex":"https://openalex.org/W4387005287","doi":"https://doi.org/10.1109/e-science58273.2023.10254908"},"language":"en","primary_location":{"id":"doi:10.1109/e-science58273.2023.10254908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/e-science58273.2023.10254908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 19th International Conference on e-Science (e-Science)","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/A5069342770","display_name":"Vincent Scheltjens","orcid":"https://orcid.org/0000-0002-6382-5750"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Vincent Scheltjens","raw_affiliation_strings":["KU Leuven, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Department of Electrical Engineering (ESAT),Leuven,Belgium,3001","Faculty of Economics and Business, KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Department of Electrical Engineering (ESAT),Leuven,Belgium,3001","institution_ids":["https://openalex.org/I99464096"]},{"raw_affiliation_string":"Faculty of Economics and Business, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102960218","display_name":"Lyse Naomi Wamba Momo","orcid":"https://orcid.org/0000-0002-9019-0236"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Lyse Naomi Wamba Momo","raw_affiliation_strings":["KU Leuven, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Department of Electrical Engineering (ESAT),Leuven,Belgium,3001"],"affiliations":[{"raw_affiliation_string":"KU Leuven, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Department of Electrical Engineering (ESAT),Leuven,Belgium,3001","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075484247","display_name":"Wouter Verbeke","orcid":"https://orcid.org/0000-0002-8438-0535"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Wouter Verbeke","raw_affiliation_strings":["KU Leuven,Faculty of Economics and Business,Leuven,Belgium,3000"],"affiliations":[{"raw_affiliation_string":"KU Leuven,Faculty of Economics and Business,Leuven,Belgium,3000","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018814006","display_name":"Bart De Moor","orcid":"https://orcid.org/0000-0002-1154-5028"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Bart De Moor","raw_affiliation_strings":["KU Leuven, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Department of Electrical Engineering (ESAT),Leuven,Belgium,3001"],"affiliations":[{"raw_affiliation_string":"KU Leuven, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics,Department of Electrical Engineering (ESAT),Leuven,Belgium,3001","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069342770"],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":0.6983,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75876747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.98089998960495,"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/computer-science","display_name":"Computer science","score":0.7801803946495056},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7444108724594116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6042789816856384},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5669925808906555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5270816683769226},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.49150192737579346},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4476076662540436},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4464961290359497},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4271281063556671},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.41371795535087585},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.41083869338035583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7801803946495056},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7444108724594116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6042789816856384},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5669925808906555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5270816683769226},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.49150192737579346},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4476076662540436},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4464961290359497},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4271281063556671},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.41371795535087585},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.41083869338035583},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"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},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/e-science58273.2023.10254908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/e-science58273.2023.10254908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 19th International Conference on e-Science (e-Science)","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/726028","is_oa":false,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/726028","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2023 IEEE International Conference on e-Science, Limassol, Cyprus, 9-13 October 2023","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2286041663","display_name":null,"funder_award_id":"C16/15/059,C3/19/053,C24/18/022,C3/20/117,C3I-21-00316","funder_id":"https://openalex.org/F4320322308","funder_display_name":"KU Leuven"},{"id":"https://openalex.org/G2449157740","display_name":null,"funder_award_id":"G0F6718N","funder_id":"https://openalex.org/F4320316161","funder_display_name":"European Orthodontic Society"},{"id":"https://openalex.org/G6656896088","display_name":null,"funder_award_id":"885682","funder_id":"https://openalex.org/F4320338335","funder_display_name":"H2020 European Research Council"}],"funders":[{"id":"https://openalex.org/F4320316161","display_name":"European Orthodontic Society","ror":null},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320322308","display_name":"KU Leuven","ror":"https://ror.org/05f950310"},{"id":"https://openalex.org/F4320327317","display_name":"Kom op tegen Kanker","ror":null},{"id":"https://openalex.org/F4320327336","display_name":"Vlaamse regering","ror":null},{"id":"https://openalex.org/F4320335809","display_name":"Departement Economie, Wetenschap en Innovatie","ror":null},{"id":"https://openalex.org/F4320338335","display_name":"H2020 European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1490324987","https://openalex.org/W2064675550","https://openalex.org/W2076530146","https://openalex.org/W2157331557","https://openalex.org/W2162800060","https://openalex.org/W2739220786","https://openalex.org/W2755364614","https://openalex.org/W2768282280","https://openalex.org/W2798720628","https://openalex.org/W2891400669","https://openalex.org/W2897093100","https://openalex.org/W2897230576","https://openalex.org/W2979637109","https://openalex.org/W3012501605","https://openalex.org/W3038426846","https://openalex.org/W3042777221","https://openalex.org/W3044211235","https://openalex.org/W3086590218","https://openalex.org/W3093755649","https://openalex.org/W3102449016","https://openalex.org/W3103802018","https://openalex.org/W3105122387","https://openalex.org/W3119198663","https://openalex.org/W3133599480","https://openalex.org/W3182739741","https://openalex.org/W3196371845","https://openalex.org/W3204012185","https://openalex.org/W4213029780","https://openalex.org/W4224278425","https://openalex.org/W4308641264","https://openalex.org/W4311088854","https://openalex.org/W4318619660","https://openalex.org/W6728757088","https://openalex.org/W6746052068","https://openalex.org/W6781232731","https://openalex.org/W6786061324","https://openalex.org/W6810362061","https://openalex.org/W6840086105","https://openalex.org/W6983582096"],"related_works":["https://openalex.org/W3189884647","https://openalex.org/W2884834684","https://openalex.org/W2917165927","https://openalex.org/W4385950391","https://openalex.org/W3123614577","https://openalex.org/W3023917431","https://openalex.org/W4311802502","https://openalex.org/W1998320186","https://openalex.org/W3192139338","https://openalex.org/W2902043866"],"abstract_inverted_index":{"Machine":[0],"and":[1,7,14,47,57,89,117,169,249],"deep":[2],"learning":[3],"methods":[4,21],"for":[5,44,106,206],"medical":[6,33],"healthcare":[8],"applications":[9],"have":[10],"shown":[11],"significant":[12],"progress":[13],"performance":[15,189],"improvement":[16],"in":[17,31,138,227,244],"recent":[18],"years.":[19],"These":[20],"require":[22],"vast":[23,40],"amounts":[24,41],"of":[25,42,55,76,102,120,145,148,181,203,210,246],"training":[26,121,202,250],"data":[27,43,56,214],"which":[28,45],"are":[29],"available":[30],"the":[32,53,96,100,139,153,166,173,197,201,224,241],"sector,":[34],"albeit":[35],"decentralized.":[36],"Medical":[37],"institutions":[38],"generate":[39],"sharing":[46],"centralizing":[48],"remains":[49],"a":[50,73,103,143,160,179],"challenge":[51],"as":[52],"result":[54],"privacy":[58],"regulations.":[59],"Federated":[60],"Learning":[61],"(FL)":[62],"is":[63],"well-suited":[64],"to":[65,80,99,152,200],"tackle":[66],"these":[67],"challenges.":[68],"However,":[69],"FL":[70],"comes":[71],"with":[72,240],"new":[74],"set":[75,144],"open":[77],"problems":[78],"related":[79],"communication":[81,115],"overhead,":[82],"efficient":[83],"parameter":[84],"aggregation,":[85],"client":[86,109,161,174],"selection":[87],"strategies":[88],"more.":[90],"In":[91,155],"this":[92,156],"work,":[93,157],"we":[94,158,221],"address":[95],"step":[97],"prior":[98],"initiation":[101],"federated":[104,204,237],"network":[105],"model":[107,188],"training,":[108],"recruitment.":[110],"By":[111,195],"intelligently":[112],"recruiting":[113],"clients,":[114],"overhead":[116],"overall":[118],"cost":[119],"can":[122,183],"be":[123,184],"reduced":[124],"without":[125,186],"sacrificing":[126,187],"predictive":[127,247],"performance.":[128],"Client":[129],"recruitment":[130,162,198],"aims":[131],"at":[132,172],"pre-excluding":[133],"potential":[134],"clients":[135,182,234],"from":[136,215,231],"partaking":[137],"federation":[140],"based":[141],"on":[142],"criteria":[146],"indicative":[147],"their":[149],"eventual":[150],"contributions":[151],"federation.":[154],"propose":[159],"approach":[163,199],"using":[164,213],"only":[165,232],"output":[167],"distribution":[168],"sample":[170],"size":[171],"site.":[175],"We":[176],"show":[177,222],"how":[178,223],"subset":[180],"recruited":[185,233],"whilst":[190],"significantly":[191,235],"improving":[192],"computation":[193],"time.":[194,251],"applying":[196],"models":[205,225,238],"accurate":[207],"patient":[208],"Length":[209],"Stay":[211],"prediction":[212],"189":[216],"intensive":[217],"care":[218],"units":[219],"(clients),":[220],"trained":[226,239],"federations":[228],"made":[229],"up":[230],"outperform":[236],"standard":[242],"procedure":[243],"terms":[245],"power":[248]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}