{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:39:23Z","timestamp":1776400763438,"version":"3.51.2"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"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":["61876046"],"award-info":[{"award-number":["61876046"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Medico-Engineering Cooperation Funds from the University of Electronic Science and Technology of China","award":["ZYGX2022YGRH009"],"award-info":[{"award-number":["ZYGX2022YGRH009"]}]},{"name":"Medico-Engineering Cooperation Funds from the University of Electronic Science and Technology of China","award":["ZYGX2022YGRH014"],"award-info":[{"award-number":["ZYGX2022YGRH014"]}]},{"name":"Guangxi \u201cBagui\u201d Teams for Innovation and Research, China"},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["GECR-2022-00430"],"award-info":[{"award-number":["GECR-2022-00430"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1109\/tmi.2022.3188728","type":"journal-article","created":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T19:22:16Z","timestamp":1657048936000},"page":"2032-2043","source":"Crossref","is-referenced-by-count":78,"title":["FedNI: Federated Graph Learning With Network Inpainting for Population-Based Disease Prediction"],"prefix":"10.1109","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9831-2787","authenticated-orcid":false,"given":"Liang","family":"Peng","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"given":"Nan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, East China Normal University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1648-6055","authenticated-orcid":false,"given":"Nicha","family":"Dvornek","sequence":"additional","affiliation":[{"name":"Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6840-0578","authenticated-orcid":false,"given":"Xiaofeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8833-0244","authenticated-orcid":false,"given":"Xiaoxiao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101765"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_2"},{"key":"ref12","first-page":"191","article-title":"Health insurance portability and accountability act of 1996","volume":"104","author":"act","year":"1996","journal-title":"Public Law"},{"key":"ref34","article-title":"Differentiable augmentation for data-efficient GAN training","author":"zhao","year":"2020","journal-title":"arXiv 2006 10738"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467185"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2013.78"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01506-3"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1561\/0400000042","article-title":"The algorithmic foundations of differential privacy","volume":"9","author":"dwork","year":"2014","journal-title":"Found Trends Theor Comput Sci"},{"key":"ref31","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016","journal-title":"arXiv 1609 02907"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32692-0_16"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-57959-7"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2018.06.001"},{"key":"ref32","first-page":"1025","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"2017","journal-title":"Proc NIPS"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1111\/cns.12499"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2021.01.002"},{"key":"ref17","article-title":"FedGraphNN: A federated learning system and benchmark for graph neural networks","author":"he","year":"2021","journal-title":"arXiv 2104 07145"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2010.00013"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2021.10.023"},{"key":"ref38","year":"2003","journal-title":"Alzheimer's Disease Neuoroimaging Initiative (ADNI)"},{"key":"ref19","article-title":"Subgraph federated learning with missing neighbor generation","author":"zhang","year":"2021","journal-title":"arXiv 2106 13430"},{"key":"ref18","author":"hanneman","year":"2005","journal-title":"Introduction to social network methods"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.104096"},{"key":"ref23","article-title":"Spectral normalization for generative adversarial networks","author":"miyato","year":"2018","journal-title":"arXiv 1802 05957"},{"key":"ref26","first-page":"1603","article-title":"Multivariate time series imputation with generative adversarial networks","author":"luo","year":"2018","journal-title":"Proc 32nd Int Conf Neural Inf Process Syst"},{"key":"ref25","article-title":"Why not to use zero imputation? Correcting sparsity bias in training neural networks","author":"yi","year":"2019","journal-title":"arXiv 1906 00150"},{"key":"ref20","article-title":"Transfer learning of graph neural networks with ego-graph information maximization","author":"zhu","year":"2020","journal-title":"arXiv 2009 05204"},{"key":"ref42","first-page":"499","article-title":"Proinflammatory and regulatory cytokine levels in AIDS cachexia","volume":"13","author":"baronzio","year":"1999","journal-title":"Vivo Athens Greece"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.01.021"},{"key":"ref22","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2017","journal-title":"Proc Artif Intell Statist"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.11.016"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.07.013"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.10.045"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106854"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32692-0_44"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.01.031"},{"key":"ref9","first-page":"1","article-title":"Recurrrent neural network based model for autism spectrum disorder prediction using codon encoding","volume":"103","author":"sudha","year":"2021","journal-title":"J Inst Eng India"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59728-3_55"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2974997"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00931-1_37"},{"key":"ref5","first-page":"414","article-title":"Graph convolutional neural networks for Alzheimer’s disease classification","author":"song","year":"2019","journal-title":"Proc IEEE 16th Int Symp Biomed Imag (ISBI)"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/42.668698"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/10168838\/09815303.pdf?arnumber=9815303","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T19:53:30Z","timestamp":1743796410000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9815303\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7]]},"references-count":42,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2022.3188728","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7]]}}}