{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T17:06:19Z","timestamp":1776272779769,"version":"3.50.1"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tkde.2022.3181780","type":"journal-article","created":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T20:53:58Z","timestamp":1655153638000},"page":"1-12","source":"Crossref","is-referenced-by-count":14,"title":["Time-aware Context-Gated Graph Attention Network for Clinical Risk Prediction"],"prefix":"10.1109","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4503-4098","authenticated-orcid":false,"given":"Yuyang","family":"Xu","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7832-2518","authenticated-orcid":false,"given":"Haochao","family":"Ying","sequence":"additional","affiliation":[{"name":"School of Public Health, Zhejiang University, Hangzhou, China"}]},{"given":"Siyi","family":"Qian","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9170-7009","authenticated-orcid":false,"given":"Fuzhen","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0824-9284","authenticated-orcid":false,"given":"Xiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Qingdao, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6441-4390","authenticated-orcid":false,"given":"Deqing","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beihang University, Beijing, China"}]},{"given":"Jian","family":"Wu","sequence":"additional","affiliation":[{"name":"Second Affiliated Hospital School of Medicine, School of Public Health, and Institute of Wenzhou, Zhejiang University, Hangzhou, China"}]},{"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Thrust, The Hong Kong University of Science and Technology, Guangzhou, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271805"},{"key":"ref12","article-title":"MedGCN: Graph convolutional networks for multiple medical tasks","author":"mao","year":"2019"},{"key":"ref15","first-page":"1263","article-title":"Neural message passing for quantum chemistry","author":"gilmer","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3007835"},{"key":"ref11","first-page":"5998","article-title":"Attention is all you need","volume":"30","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403107"},{"key":"ref17","article-title":"Gated graph sequence neural networks","author":"li","year":"2015"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref19","first-page":"339","article-title":"GaAN: Gated attention networks for learning on large and spatiotemporal graphs","author":"zhang","year":"2018","journal-title":"Proc Conf Uncertainty of Artificial Intelligence"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272010"},{"key":"ref50","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/825"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098109"},{"key":"ref42","first-page":"3452","article-title":"AttDMM: An attentive deep Markov model for risk scoring in intensive care units","author":"\u00f6zyurt","year":"2021","journal-title":"Proc ACM SIGKDD Int Conf Knowledge Discovery and Data Mining"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00196"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2020.100174"},{"key":"ref43","article-title":"PREMIER: Personalized recommendation for medical prescriptions from electronic records","author":"bhoi","year":"2020"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/641"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3025813"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5440"},{"key":"ref9","article-title":"Clinical risk prediction with temporal probabilistic asymmetric multi-task learning","author":"nguyen","year":"2020"},{"key":"ref4","first-page":"1","article-title":"Multitask learning and benchmarking with clinical time series data","volume":"6","author":"harutyunyan","year":"2019","journal-title":"Data Science Journal"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/nrg3208","article-title":"Mining electronic health records: Towards better research applications and clinical care","volume":"13","author":"jensen","year":"2012","journal-title":"Nature Rev Genet"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097997"},{"key":"ref5","first-page":"3512","article-title":"RETAIN: An interpretable predictive model for healthcare using reverse time attention mechanism","author":"choi","year":"2016","journal-title":"Proc 30th Int Conf Neural Inf Process Syst"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449860"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5428"},{"key":"ref34","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411864"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5427"},{"key":"ref31","first-page":"609","article-title":"A learning rule for asynchronous perceptrons with feedback in a combinatorial environment","author":"almeida","year":"1987","journal-title":"Proc IEEE Int Conf Neural Netw"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref33","first-page":"2014","article-title":"Learning convolutional neural networks for graphs","author":"niepert","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.59.2229"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3127881"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocy068"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11635"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219904"},{"key":"ref24","article-title":"MIMIC-III, a freely accessible critical care database","volume":"3","author":"johnson","year":"2016","journal-title":"Data Science Journal"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1161\/01.CIR.101.23.e215"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2981333"},{"key":"ref20","article-title":"Graph attention networks","volume":"1050","author":"veli?kovi?","year":"2018","journal-title":"Stat"},{"key":"ref22","first-page":"1","article-title":"The eICU collaborative research database, a freely available multi-center database for critical care research","volume":"5","author":"pollard","year":"2018","journal-title":"Data Science Journal"},{"key":"ref21","article-title":"MIMIC-IV (version 1.0)","author":"johnson","year":"2020"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330779"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402736"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/4358933\/09794568.pdf?arnumber=9794568","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,7]],"date-time":"2023-06-07T01:40:03Z","timestamp":1686102003000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9794568\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/tkde.2022.3181780","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}