{"id":"https://openalex.org/W4385338552","doi":"https://doi.org/10.1109/tnnls.2023.3297103","title":"MetaFed: Federated Learning Among Federations With Cyclic Knowledge Distillation for Personalized Healthcare","display_name":"MetaFed: Federated Learning Among Federations With Cyclic Knowledge Distillation for Personalized Healthcare","publication_year":2023,"publication_date":"2023-07-28","ids":{"openalex":"https://openalex.org/W4385338552","doi":"https://doi.org/10.1109/tnnls.2023.3297103","pmid":"https://pubmed.ncbi.nlm.nih.gov/37506019"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3297103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3297103","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5008558592","display_name":"Yiqiang Chen","orcid":"https://orcid.org/0000-0002-8407-0780"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqiang Chen","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8407-0780","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100774978","display_name":"Lu Wang","orcid":"https://orcid.org/0000-0003-4035-0737"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Lu","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4035-0737","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023273288","display_name":"Xin Qin","orcid":"https://orcid.org/0000-0002-4717-4310"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Qin","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4717-4310","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700956","display_name":"Jindong Wang","orcid":"https://orcid.org/0000-0002-4833-0880"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jindong Wang","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4833-0880","affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8608-8482","affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.3557,"has_fulltext":false,"cited_by_count":103,"citation_normalized_percentile":{"value":0.99226465,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"35","issue":"11","first_page":"16671","last_page":"16682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9976000189781189,"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":0.9976000189781189,"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/T11446","display_name":"Mobile Health and mHealth Applications","score":0.9314000010490417,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"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/federated-learning","display_name":"Federated learning","score":0.8374183177947998},{"id":"https://openalex.org/keywords/distrust","display_name":"Distrust","score":0.8030021786689758},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.7296074628829956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7146560549736023},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6768908500671387},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.552112877368927},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4698787033557892},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.45604661107063293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2451786994934082},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.21988672018051147},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13121125102043152},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09266218543052673}],"concepts":[{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8374183177947998},{"id":"https://openalex.org/C2778321746","wikidata":"https://www.wikidata.org/wiki/Q621922","display_name":"Distrust","level":2,"score":0.8030021786689758},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.7296074628829956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7146560549736023},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6768908500671387},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.552112877368927},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4698787033557892},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.45604661107063293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2451786994934082},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.21988672018051147},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13121125102043152},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09266218543052673},{"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019359","descriptor_name":"Knowledge","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019359","descriptor_name":"Knowledge","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019359","descriptor_name":"Knowledge","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019359","descriptor_name":"Knowledge","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057285","descriptor_name":"Precision Medicine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057285","descriptor_name":"Precision Medicine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057285","descriptor_name":"Precision Medicine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D057285","descriptor_name":"Precision Medicine","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3297103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3297103","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37506019","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37506019","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1636353083","display_name":null,"funder_award_id":"62202455","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6956636849","display_name":null,"funder_award_id":"Z221100002722009","funder_id":"https://openalex.org/F4320325902","funder_display_name":"Beijing Municipal Science and Technology Commission"},{"id":"https://openalex.org/G8567002948","display_name":"\u9762\u5411\u5e15\u91d1\u68ee\u65e9\u671f\u9884\u8b66\u7684\u8054\u90a6\u8fc1\u79fb\u5b66\u4e60\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61972383","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"},{"id":"https://openalex.org/F4320325902","display_name":"Beijing Municipal Science and Technology Commission","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1690739335","https://openalex.org/W1821462560","https://openalex.org/W2026297770","https://openalex.org/W2112796928","https://openalex.org/W2113959942","https://openalex.org/W2145954079","https://openalex.org/W2167366427","https://openalex.org/W2736191430","https://openalex.org/W2743937022","https://openalex.org/W2744999500","https://openalex.org/W2763549966","https://openalex.org/W2774265933","https://openalex.org/W2910094941","https://openalex.org/W2912213068","https://openalex.org/W2912564039","https://openalex.org/W2945262235","https://openalex.org/W3012211282","https://openalex.org/W3012501605","https://openalex.org/W3018464563","https://openalex.org/W3035927627","https://openalex.org/W3040617750","https://openalex.org/W3042050487","https://openalex.org/W3086590218","https://openalex.org/W3095948197","https://openalex.org/W3125717455","https://openalex.org/W3127512060","https://openalex.org/W3128131898","https://openalex.org/W3133814152","https://openalex.org/W3138986594","https://openalex.org/W3144030700","https://openalex.org/W3164330620","https://openalex.org/W3164573547","https://openalex.org/W3186759331","https://openalex.org/W3187378100","https://openalex.org/W3194273732","https://openalex.org/W4214837566","https://openalex.org/W4214892882","https://openalex.org/W4221150580","https://openalex.org/W4224931233","https://openalex.org/W4226458186","https://openalex.org/W4249888301","https://openalex.org/W4282979157","https://openalex.org/W4283800079","https://openalex.org/W4285229324","https://openalex.org/W4287868747","https://openalex.org/W4288054906","https://openalex.org/W4295308569","https://openalex.org/W4310633849","https://openalex.org/W4317436377","https://openalex.org/W6637551013","https://openalex.org/W6676828653","https://openalex.org/W6684191040","https://openalex.org/W6728757088","https://openalex.org/W6758047254","https://openalex.org/W6759238902","https://openalex.org/W6763048141","https://openalex.org/W6773552689","https://openalex.org/W6779794951","https://openalex.org/W6789305514","https://openalex.org/W6790490591","https://openalex.org/W6792458728","https://openalex.org/W6800804906","https://openalex.org/W6803877844","https://openalex.org/W6839362776","https://openalex.org/W6840458696","https://openalex.org/W7011116384"],"related_works":["https://openalex.org/W2152370238","https://openalex.org/W3193570178","https://openalex.org/W3160132286","https://openalex.org/W2136955267","https://openalex.org/W2712460288","https://openalex.org/W2352717624","https://openalex.org/W2364471629","https://openalex.org/W3099737524","https://openalex.org/W4392012396","https://openalex.org/W4303448918"],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"has":[3],"attracted":[4],"increasing":[5],"attention":[6],"to":[7,28,51],"building":[8],"models":[9],"without":[10,66,115],"accessing":[11],"raw":[12],"user":[13],"data,":[14],"especially":[15],"in":[16,91,149],"healthcare.":[17],"In":[18,41],"real":[19],"applications,":[20],"different":[21,56],"federations":[22],"can":[23],"seldom":[24],"work":[25],"together":[26],"due":[27],"possible":[29],"reasons":[30],"such":[31],"as":[32,81],"data":[33],"heterogeneity":[34],"and":[35,85,105],"distrust/inexistence":[36],"of":[37,88],"the":[38,71,131],"central":[39,68],"server.":[40],"this":[42],"article,":[43],"we":[44],"propose":[45],"a":[46,60,67,82,92,116],"novel":[47],"framework":[48],"called":[49],"MetaFed":[50,58,77,114,145],"facilitate":[52],"trustworthy":[53],"FL":[54],"between":[55],"federations.":[57],"obtains":[59],"personalized":[61],"model":[62],"for":[63,133],"each":[64,79,89],"federation":[65,80,90],"server":[69,117],"via":[70],"proposed":[72],"cyclic":[73,93],"knowledge":[74,87,103],"distillation.":[75],"Specifically,":[76],"treats":[78],"meta":[83],"distribution":[84],"aggregates":[86],"manner.":[94],"The":[95],"training":[96],"is":[97],"split":[98],"into":[99],"two":[100],"parts:":[101],"common":[102],"accumulation":[104],"personalization.":[106],"Comprehensive":[107],"experiments":[108],"on":[109],"seven":[110],"benchmarks":[111],"demonstrate":[112],"that":[113],"achieves":[118],"better":[119],"accuracy":[120,127],"compared":[121,129],"with":[122,130,139],"state-of-the-art":[123],"methods":[124],"[e.g.,":[125],"10%+":[126],"improvement":[128],"baseline":[132],"physical":[134],"activity":[135],"monitoring":[136],"dataset":[137],"(PAMAP2)]":[138],"fewer":[140],"communication":[141],"costs.":[142],"More":[143],"importantly,":[144],"shows":[146],"remarkable":[147],"performance":[148],"real-healthcare-related":[150],"applications.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":49},{"year":2024,"cited_by_count":35},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}