{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T21:05:41Z","timestamp":1775595941655,"version":"3.50.1"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"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":["62302471"],"award-info":[{"award-number":["62302471"]}],"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":[[2026,4]]},"DOI":"10.1109\/jbhi.2025.3613485","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T17:34:05Z","timestamp":1758735245000},"page":"3013-3026","source":"Crossref","is-referenced-by-count":0,"title":["WN-Sleep: Modeling Whole-Night Data for Improved Sleep Staging Classification"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9786-0850","authenticated-orcid":false,"given":"Fang","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6941-981X","authenticated-orcid":false,"given":"Zhi","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7097-4837","authenticated-orcid":false,"given":"Zhi","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"given":"Gaohan","family":"Ye","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"given":"Lingjie","family":"Shu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"given":"Yu","family":"Pu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"given":"Beilei","family":"Wang","sequence":"additional","affiliation":[{"name":"First Affiliated Hospital of USTC, Anhui Provincial Hospital, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7254-5877","authenticated-orcid":false,"given":"Dong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6309-6626","authenticated-orcid":false,"given":"Dongheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0379-1525","authenticated-orcid":false,"given":"Yang","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3227-4562","authenticated-orcid":false,"given":"Yan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1062856"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0301-0511(01)00090-4"},{"issue":"2012","key":"ref3","article-title":"The AASM manual for the scoring of sleep and associated events","volume-title":"Rules, Terminol. Tech. Specifications, Darien, Illinois, Amer. Acad. Sleep Med.","volume":"176","author":"Berry","year":"2012"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-8986.1979.tb02991.x"},{"key":"ref5","first-page":"12449","article-title":"wav2vec 2.0: A framework for self-supervised learning of speech representations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Baevski","year":"2020"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3284160"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2021.3076234"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2024.3426939"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1093\/sleep\/20.12.1077"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3198997"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2017.2721116"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2019.2896659"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3070057"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3303197"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocy064"},{"key":"ref17","article-title":"Efficiently modeling long sequences with structured state spaces","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Gu","year":"2022"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2978004"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.3037693"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3494961"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocy131"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2023.3309542"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3157262"},{"key":"ref24","article-title":"Automatic sleep stage scoring with single-channel EEG using convolutional neural networks","author":"Tsinalis","year":"2016"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2018.2813138"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8512286"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3208314"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3332503"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3330345"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2024.3422472"},{"key":"ref32","first-page":"4415","article-title":"U-Time: A fully convolutional network for time series segmentation applied to sleep staging","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","volume":"32","author":"Perslev","year":"2019"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00440-5"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2022.3147187"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref37","article-title":"Gaussian error linear units (GELUs)","author":"Hendrycks","year":"2016"},{"key":"ref38","first-page":"1474","article-title":"Hippo: Recurrent memory with optimal polynomial projections","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Gu","year":"2020"},{"key":"ref39","first-page":"572","article-title":"Combining recurrent, convolutional, and continuous-time models with linear state-space layers","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Gu","year":"2021"},{"key":"ref40","first-page":"22982","article-title":"Diagonal state spaces are as effective as structured state spaces","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Gupta","year":"2022"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2607"},{"key":"ref42","first-page":"3800","article-title":"Improving the gating mechanism of recurrent neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gu","year":"2020"},{"key":"ref43","article-title":"Gated linear attention transformers with hardware-efficient training","volume-title":"Proc. 41st Int. Conf. Mach. Learn.","author":"Yang","year":"2024"},{"key":"ref44","article-title":"Mega: Moving average equipped gated attention","author":"Ma","year":"2022"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2021.3117616"},{"key":"ref46","first-page":"1","article-title":"Gradient gating for deep multi-rate learning on graphs","volume-title":"Proc. Int. Conf. Learn. Representations","volume":"9","author":"Rusch","year":"2023"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104425"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/10.867928"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1161\/01.CTR.101.23.e215"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.11613\/BM.2012.031"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/312624.312647"},{"key":"ref52","first-page":"1","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","year":"2014"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2019.2962673"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2668"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.mayocp.2017.09.007"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1053\/smrv.2001.0245"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.5665\/sleep.2802"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1093\/sleep\/zsx117"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref60","article-title":"Simplified state space layers for sequence modeling","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Smith","year":"2023"},{"key":"ref61","article-title":"Mamba:","volume-title":"Proc. Ist Conf. Lang. Model.","author":"Gu","year":"2024"},{"key":"ref62","first-page":"838","article-title":"Precision-recall-gain curves: Pr analysis done right","volume-title":"Proc. 29th Int. Conf. Neural Inf. Process. Syst.","volume":"28","author":"Flach","year":"2015"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s00415-018-9095-1"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109082"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2023.3252577"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2024.103961"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.111543"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.113522"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221020\/11475574\/11177565.pdf?arnumber=11177565","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T20:01:38Z","timestamp":1775592098000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11177565\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":68,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2025.3613485","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]}}}