{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T03:58:50Z","timestamp":1788667130858,"version":"build-2803163510"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Technologies R&D Program","award":["2017YFB1002502"],"award-info":[{"award-number":["2017YFB1002502"]}]},{"name":"General Program of Nature Science Foundation of China","award":["61977010"],"award-info":[{"award-number":["61977010"]}]},{"name":"Beijing Advanced Education Center for Future Education","award":["BJAICFE2016IR-003"],"award-info":[{"award-number":["BJAICFE2016IR-003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1109\/jbhi.2019.2940695","type":"journal-article","created":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T19:37:08Z","timestamp":1568230628000},"page":"1677-1685","source":"Crossref","is-referenced-by-count":40,"title":["Decoding Brain States From fMRI Signals by Using Unsupervised Domain Adaptation"],"prefix":"10.1109","volume":"24","author":[{"given":"Yufei","family":"Gao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yameng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7136-5774","authenticated-orcid":false,"given":"Zhiyuan","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2744-1474","authenticated-orcid":false,"given":"Xiaojuan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5508-1165","authenticated-orcid":false,"given":"Jiacai","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.04.127"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.09.048"},{"key":"ref33","article-title":"A transfer learning approach for classification of clinical significant prostate cancers from mpMRI scans","volume":"10134","author":"chen","year":"2017","journal-title":"Proc SPIE"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2482920"},{"key":"ref31","first-page":"4058","article-title":"Wasserstein distance guided representation learning for domain adaptation","author":"shen","year":"2017","journal-title":"Proc 32nd AAAI Conf Artif Intell"},{"key":"ref30","first-page":"165","article-title":"Label efficient learning of transferable representations across domains and tasks","author":"luo","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.05.033"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.05.041"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2907040"},{"key":"ref34","article-title":"PnP-AdaNet: Plug-and-play adversarial domain adaptation network with a benchmark at cross-modality cardiac segmentation","author":"dou","year":"2018"},{"key":"ref28","first-page":"677","article-title":"Transfer learning via dimensionality reduction","volume":"8","author":"pan","year":"2008","journal-title":"Proc 23rd Nat Conf Artif Intell"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.03.026"},{"key":"ref29","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","volume":"70","author":"long","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2010.00028"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.0548-14.2014"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071516-044442"},{"key":"ref22","article-title":"Interpretable LSTMs for whole-brain neuroimaging analyses","author":"thomas","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00931-1_37"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.12.011"},{"key":"ref23","author":"bishop","year":"2006","journal-title":"Pattern Recognition and Machine Learning"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.02.083"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhs352"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.01.025"},{"key":"ref51","first-page":"3320","article-title":"How transferable are features in deep neural networks?","author":"yosinski","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref57","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1321728111"},{"key":"ref52","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","volume":"37","author":"long","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.07.037"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1126\/science.1063736"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.10062"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.460020402"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.95.3.803"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0600244103"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.12.099"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2012.10.014"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1162\/jocn_a_00189"},{"key":"ref18","article-title":"Deep learning of fMRI big data: A novel approach to subject-transfer decoding","author":"koyamada","year":"2015"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00931-1_21"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1167\/10.5.25"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4174"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-018-9358-0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2013.08.020"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1038\/nature14445"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1302-13.2014"},{"key":"ref49","first-page":"1718","article-title":"Generative moment matching networks","author":"li","year":"2015","journal-title":"Proc Int Conf Int Conf Mach Learn"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.23015"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-76153-9_28"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref48","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"gretton","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref47","first-page":"2096","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref42","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2010.00013"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"ref43","first-page":"3642","article-title":"Multi-column deep neural networks for image classification","author":"cire?an","year":"2012","journal-title":"Proc IEEE Conf Comput Vision Pattern Recognit"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/9108313\/08832215.pdf?arnumber=8832215","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:19:58Z","timestamp":1651079998000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8832215\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6]]},"references-count":57,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2019.2940695","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6]]}}}