{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T11:36:31Z","timestamp":1785324991545,"version":"3.55.0"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"JSPS Grant-in-Aid for Scientific Research","award":["23K11103"],"award-info":[{"award-number":["23K11103"]}]},{"name":"NEC C&C Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Sustain. Comput."],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1109\/tsusc.2023.3279111","type":"journal-article","created":{"date-parts":[[2023,5,23]],"date-time":"2023-05-23T18:46:32Z","timestamp":1684867592000},"page":"694-702","source":"Crossref","is-referenced-by-count":74,"title":["Blockchain-Based Personalized Federated Learning for Internet of Medical Things"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2938-6368","authenticated-orcid":false,"given":"Zhuotao","family":"Lian","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5879-585X","authenticated-orcid":false,"given":"Weizheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1416-4677","authenticated-orcid":false,"given":"Zhaoyang","family":"Han","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6461-9684","authenticated-orcid":false,"given":"Chunhua","family":"Su","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944481"},{"key":"ref35","article-title":"Improving federated learning personalization via model agnostic meta learning","author":"jiang","year":"2019"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207469"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3160699"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000286"},{"key":"ref37","article-title":"Federated meta-learning: Democratizing algorithm selection across disciplines and software libraries","author":"arambakam","year":"2020","journal-title":"Proc 7th ICML Workshop Automated Mach Learn"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/WorldS450073.2020.9210355"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2020.2988604"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-69250-1","article-title":"Federated learning in medicine: Facilitating multi-institutional collaborations without sharing patient data","volume":"10","author":"sheller","year":"2020","journal-title":"Sci Rep"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03583-3"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155494"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3501296"},{"key":"ref10","article-title":"Federated learning with non-IID data","author":"zhao","year":"2018"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-021-00337-8"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/2487759"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2020.3045266"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2020.2973651"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3105682"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/BlackSeaCom.2019.8812784"},{"key":"ref38","article-title":"Federated learning with personalization layers","author":"arivazhagan","year":"2019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2849014"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2977383"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2021.09.010"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00023"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2021.3112693"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3058953"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3027440"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2023.3239391"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2019.12.030"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.001.1900119"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000263"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3117762"},{"key":"ref44","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/WOCN.2012.6335565"},{"key":"ref43","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"xiao","year":"2017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3383455.3422562"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3128559"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_17"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/LCN.Workshops.2017.72"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761381"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3172310"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE.2019.8861593"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcot.2020.05.011"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.13173"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3150363"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2942190"}],"container-title":["IEEE Transactions on Sustainable Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274860\/10352167\/10132014.pdf?arnumber=10132014","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T19:57:09Z","timestamp":1702497429000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10132014\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10]]},"references-count":47,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tsusc.2023.3279111","relation":{},"ISSN":["2377-3782","2377-3790"],"issn-type":[{"value":"2377-3782","type":"electronic"},{"value":"2377-3790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10]]}}}