{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T00:34:20Z","timestamp":1726014860891},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,30]]},"DOI":"10.1109\/ijcnn60899.2024.10650102","type":"proceedings-article","created":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T17:35:05Z","timestamp":1725903305000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["SWGP: Semi-supervised clustering via Wasserstein generative adversarial network with gradient penalty for uncovering brain disease heterogeneity from medical images"],"prefix":"10.1109","author":[{"given":"Shaopeng","family":"Wei","sequence":"first","affiliation":[{"name":"USTC,School of Data Science,Hefei,China"}]},{"given":"Canhong","family":"Wen","sequence":"additional","affiliation":[{"name":"USTC,School of Management,Hefei,China"}]},{"given":"Haizhu","family":"Tan","sequence":"additional","affiliation":[{"name":"Shantou University,Medical College,Shantou,China"}]},{"given":"Chiyu","family":"Wei","sequence":"additional","affiliation":[{"name":"Shantou University,Medical College,Shantou,China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.01.056"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2007.08.006"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.tins.2011.05.005"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(11)70156-9"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000001003"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1001\/archneur.64.8.1130"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.02.079"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/alz.12178"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611073113"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-0716-3195-9_16"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-05892-0"},{"article-title":"Surreal-gan:semi-supervised representation learning via gan for uncovering heterogeneous diseaserelated imaging patterns","year":"2022","author":"Yang","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.02.041"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2487423"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102304"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1002\/alz.052735"},{"article-title":"Towards principled methods for training generative adversarial networks","year":"2017","author":"Arjovsky","key":"ref17"},{"journal-title":"Optimal transport : old and new. Optimal transport : old and new","year":"2014","author":"Villani","key":"ref18"},{"article-title":"Wasserstein gan","year":"2017","author":"Arjovsky","key":"ref19"},{"article-title":"Improved training of wasserstein gans","year":"2017","author":"Gulrajani","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/42.668698"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2013.09.010"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.11.073"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/0105003"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"}],"event":{"name":"2024 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2024,6,30]]},"location":"Yokohama, Japan","end":{"date-parts":[[2024,7,5]]}},"container-title":["2024 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10649807\/10649898\/10650102.pdf?arnumber=10650102","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T04:49:16Z","timestamp":1725943756000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10650102\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,30]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/ijcnn60899.2024.10650102","relation":{},"subject":[],"published":{"date-parts":[[2024,6,30]]}}}