{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:51:36Z","timestamp":1774540296781,"version":"3.50.1"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"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":["81801940"],"award-info":[{"award-number":["81801940"]}],"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":["6197200"],"award-info":[{"award-number":["6197200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1109\/jbhi.2023.3253208","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T18:43:40Z","timestamp":1678128220000},"page":"3049-3060","source":"Crossref","is-referenced-by-count":16,"title":["Cross-Hospital Sepsis Early Detection via Semi-Supervised Optimal Transport With Self-Paced Ensemble"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2273-8260","authenticated-orcid":false,"given":"Ruiqing","family":"Ding","sequence":"first","affiliation":[{"name":"Key Lab of High Confidence Software Technologies, Peking University, Ministry of Education, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6839-5326","authenticated-orcid":false,"given":"Yu","family":"Zhou","sequence":"additional","affiliation":[{"name":"General Intensive Care Unit, Zhejiang University School of Medicine Second Affiliated Hospital, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3264-0187","authenticated-orcid":false,"given":"Jie","family":"Xu","sequence":"additional","affiliation":[{"name":"IT Center, Zhejiang University School of Medicine Second Affiliated Hospital, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8810-0182","authenticated-orcid":false,"given":"Yan","family":"Xie","sequence":"additional","affiliation":[{"name":"Beijing HealSci Technology Company, Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0564-3681","authenticated-orcid":false,"given":"Qiqiang","family":"Liang","sequence":"additional","affiliation":[{"name":"General Intensive Care Unit, Zhejiang University School of Medicine Second Affiliated Hospital, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4795-7075","authenticated-orcid":false,"given":"He","family":"Ren","sequence":"additional","affiliation":[{"name":"Beijing HealSci Technology Company, Ltd., Beijing, China"}]},{"given":"Yixuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Peking University, Beijing, China"}]},{"given":"Yanlin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7627-8485","authenticated-orcid":false,"given":"Leye","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Lab of High Confidence Software Technologies, Peking University, Ministry of Education, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0842-2254","authenticated-orcid":false,"given":"Man","family":"Huang","sequence":"additional","affiliation":[{"name":"General Intensive Care Unit, Zhejiang University School of Medicine Second Affiliated Hospital, Hangzhou, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2012.93"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.22489\/CinC.2019.238"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref56","first-page":"1","article-title":"MIMIC-III, a freely accessible critical care database","volume":"3","author":"johnson","year":"2016","journal-title":"Data Science Journal"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s41666-019-00062-3"},{"key":"ref59","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"chung","year":"0","journal-title":"Proc NIPS Workshop Deep Learn"},{"key":"ref14","first-page":"301","article-title":"Doctor AI: Predicting clinical events via recurrent neural networks","author":"choi","year":"0","journal-title":"Proc Mach Learn Healthcare Conf"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1137\/S0036141002410927"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000004550"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s00134-019-05872-y"},{"key":"ref55","first-page":"143","article-title":"Experiments with noise filtering in a medical domain","volume":"99","author":"gamberger","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000004494"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46478-7_31"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1109\/TNN.2010.2091281","article-title":"Domain adaptation via transfer component analysis","volume":"22","author":"pan","year":"2011","journal-title":"IEEE Trans Neural Netw"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1990.03440210049031"},{"key":"ref19","first-page":"442","article-title":"Learning bounds for importance weighting","volume":"10","author":"cortes","year":"0","journal-title":"Proc Int Conf Adv Neural Inf Process Syst"},{"key":"ref18","article-title":"Regularized learning for domain adaptation under label shifts","author":"azizzadenesheli","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0288"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1161\/01.CIR.101.23.e215"},{"key":"ref46","first-page":"1189","article-title":"Self-paced learning for latent variable models","author":"kumar","year":"0","journal-title":"Proc 23rd Int Conf Adv Neural Inf Process Syst 24th Annu Conf Neural Inf Process Syst"},{"key":"ref45","first-page":"148","article-title":"Experiments with a new boosting algorithm","volume":"96","author":"freund","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2567393"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1112-4"},{"key":"ref42","first-page":"973","article-title":"The foundations of cost-sensitive learning","volume":"17","author":"elkan","year":"0","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00445"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-39804-2_12"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2881114"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0174708"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jelectrocard.2017.08.013"},{"key":"ref9","first-page":"1174","article-title":"Learning to detect sepsis with a multitask Gaussian process RNN classifier","author":"futoma","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1186\/s13054-016-1596-7"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201504-0781OC"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1097\/01.CCM.0000217961.75225.E9"},{"key":"ref5","article-title":"Temporal pattern discovery for accurate sepsis diagnosis in ICU patients","author":"sheetrit","year":"2017"},{"key":"ref40","first-page":"447","article-title":"DeepJDOT: Deep joint distribution optimal transport for unsupervised domain adaptation","author":"damodaran","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref35","first-page":"4204","article-title":"Mapping estimation for discrete optimal transport","author":"perrot","year":"0","journal-title":"Proc 30th Int Conf Neural Inf Process Syst"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44848-9_18"},{"key":"ref37","first-page":"3733","article-title":"Joint distribution optimal transportation for domain adaptation","author":"courty","year":"0","journal-title":"Proc Int 31st Int Conf Adv Neural Inf Process Syst"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-71246-8_45"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2019.2894570"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.3021662"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2615921"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000004145"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1097\/PCC.0000000000000389"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0287"},{"key":"ref39","first-page":"1","article-title":"POT: Python optimal transport","volume":"22","author":"flamary","year":"2021","journal-title":"J Mach Learn Res"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/412"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00814"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00078"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00175"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00116"},{"key":"ref20","first-page":"19290","article-title":"Rethinking the value of labels for improving class-imbalanced learning","author":"yang","year":"0","journal-title":"Proc 34th Int Conf Neural Inf Process Syst"},{"key":"ref22","volume":"338","author":"villani","year":"2008","journal-title":"Optimal Transport Old and New"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.07.011"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2861006"},{"key":"ref27","first-page":"666","article-title":"Mémoire sur la théorie des déblais et des remblais","author":"monge","year":"1781"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2019.2927463"},{"key":"ref60","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449855"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/10144459\/10061196.pdf?arnumber=10061196","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T18:44:23Z","timestamp":1687805063000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10061196\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6]]},"references-count":62,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2023.3253208","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6]]}}}