{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T20:58:26Z","timestamp":1766437106309,"version":"3.48.0"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072360"],"award-info":[{"award-number":["62072360"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172438"],"award-info":[{"award-number":["62172438"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"key Research and Development Plan of Shaanxi Province","award":["2021ZDLGY02-09"],"award-info":[{"award-number":["2021ZDLGY02-09"]}]},{"name":"key Research and Development Plan of Shaanxi Province","award":["2023-GHZD-44"],"award-info":[{"award-number":["2023-GHZD-44"]}]},{"name":"key Research and Development Plan of Shaanxi Province","award":["2023-ZDLGY-54"],"award-info":[{"award-number":["2023-ZDLGY-54"]}]},{"DOI":"10.13039\/501100014206","name":"National Key Laboratory Foundation of China","doi-asserted-by":"publisher","award":["2023-JCJQ-LB-007"],"award-info":[{"award-number":["2023-JCJQ-LB-007"]}],"id":[{"id":"10.13039\/501100014206","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Guangdong Province of China","award":["2022A1515010988"],"award-info":[{"award-number":["2022A1515010988"]}]},{"name":"Key Project on Artificial Intelligence of Xi\u2019an Science and Technology Plan","award":["23ZDCYJSGG0021-2022"],"award-info":[{"award-number":["23ZDCYJSGG0021-2022"]}]},{"name":"Key Project on Artificial Intelligence of Xi\u2019an Science and Technology Plan","award":["23ZDCYYYCJ0008"],"award-info":[{"award-number":["23ZDCYYYCJ0008"]}]},{"name":"Key Project on Artificial Intelligence of Xi\u2019an Science and Technology Plan","award":["23ZDCYJSGG0002-2023"],"award-info":[{"award-number":["23ZDCYJSGG0002-2023"]}]},{"name":"Research Program of the Liaoning Liaohe Laboratory","award":["LLL23ZZ-02-01"],"award-info":[{"award-number":["LLL23ZZ-02-01"]}]},{"name":"Research Program of the Liaoning Liaohe Laboratory","award":["LLL23ZZ-02-02"],"award-info":[{"award-number":["LLL23ZZ-02-02"]}]},{"name":"Liaoning Province\u2019s Major Science and Technology Projects","award":["2024JH1\/11700049"],"award-info":[{"award-number":["2024JH1\/11700049"]}]},{"name":"Liaoning Province\u2019s Xingliao Talent Project","award":["XLYC2403037"],"award-info":[{"award-number":["XLYC2403037"]}]},{"name":"Xidian-UTAR China Malaysia Science and Technology Institute\u2013the Fundamental Research Funds for the Central Universities","award":["XURF-2025-QTZX25087"],"award-info":[{"award-number":["XURF-2025-QTZX25087"]}]},{"name":"Xidian-UTAR China Malaysia Science and Technology Institute\u2013the Fundamental Research Funds for the Central Universities","award":["XURF-2025-QTZX25065"],"award-info":[{"award-number":["XURF-2025-QTZX25065"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Consumer Electron."],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1109\/tce.2025.3609547","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T17:33:49Z","timestamp":1758044029000},"page":"11371-11382","source":"Crossref","is-referenced-by-count":0,"title":["A Lightweight Split Federated Learning Approach With Dynamic Model Aggregation for Breast Cancer Prediction in Consumer-Centric Health Electronics"],"prefix":"10.1109","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2339-203X","authenticated-orcid":false,"given":"Jiaman","family":"Li","sequence":"first","affiliation":[{"name":"Guangzhou Institute of Technology, Xidian University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1104-5039","authenticated-orcid":false,"given":"Dapeng","family":"Lan","sequence":"additional","affiliation":[{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9302-9368","authenticated-orcid":false,"given":"Dawei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, Henan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiakai","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Neonatology, Xi&#x2019;an Children&#x2019;s Hospital, Xi&#x2019;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3811-5682","authenticated-orcid":false,"given":"Hui","family":"Han","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi&#x2019;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8173-0408","authenticated-orcid":false,"given":"Lei","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Technology, Xidian University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4971-5029","authenticated-orcid":false,"given":"Chen","family":"Chen","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Technology, Xidian University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2025.3528934"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2025.3545963"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2024.3407769"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2024.3506915"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.5306\/wjco.v5.i3.465"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng071516-044442"},{"key":"ref8","article-title":"CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning","author":"Rajpurkar","year":"2017","journal-title":"arXiv:1711.05225"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/srep26094"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3367946"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3257562"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-022-02155-w"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-80187-7"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2024.03.027"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2018.05.003"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20825"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM53939.2023.10228959"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3181823"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2025.3535753"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3564722"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-61609-0_60"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.clon.2024.03.008"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2024.047874"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-3966-0_12"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i4.28082"},{"key":"ref26","article-title":"Split learning for health: Distributed deep learning without sharing raw patient data","author":"Vepakomma","year":"2018","journal-title":"arXiv:1812.00564"},{"key":"ref27","article-title":"SLPerf: A unified framework for benchmarking split learning","author":"Zhou","year":"2023","journal-title":"arXiv:2304.01502"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-58741-0"},{"key":"ref29","first-page":"1047","article-title":"Split learning for distributed collaborative training of deep learning models in health informatics","volume-title":"Proc. AMIA Annu. Symp.","author":"Li"},{"key":"ref30","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist. (AISTATS)","author":"McMahan"},{"issue":"10","key":"ref31","first-page":"4386","article-title":"Client selection in federated learning: Principles, challenges, and opportunities","volume":"32","author":"Zhao","year":"2021","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref32","article-title":"FedPNS: Accelerating convergence in federated learning with non-IID data via node selection","author":"Liu","year":"2020","journal-title":"arXiv:2006.10100"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02264"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICNC64010.2025.10993643"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2020.2996273"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3543441"},{"key":"ref37","article-title":"FedGCS: A generative framework for efficient client selection in federated learning via gradient-based optimization","author":"Ning","year":"2024","journal-title":"arXiv:2405.06312"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447356"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2024.3411479"}],"container-title":["IEEE Transactions on Consumer Electronics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/30\/11306167\/11164890.pdf?arnumber=11164890","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T18:42:19Z","timestamp":1766428939000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11164890\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":39,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tce.2025.3609547","relation":{},"ISSN":["0098-3063","1558-4127"],"issn-type":[{"type":"print","value":"0098-3063"},{"type":"electronic","value":"1558-4127"}],"subject":[],"published":{"date-parts":[[2025,11]]}}}