{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T07:09:52Z","timestamp":1784099392304,"version":"3.55.0"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,5,24]],"date-time":"2026-05-24T00:00:00Z","timestamp":1779580800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,24]],"date-time":"2026-05-24T00:00:00Z","timestamp":1779580800000},"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":[],"published-print":{"date-parts":[[2026,5,24]]},"DOI":"10.1109\/icc59461.2026.11588033","type":"proceedings-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T19:38:09Z","timestamp":1784057889000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["CT-LSTM: Cluster-based Classification of Irregular Time-series Medical Data"],"prefix":"10.1109","author":[{"given":"Jianan","family":"Tang","sequence":"first","affiliation":[{"name":"Xi&#x2019;an Jiaotong-Liverpool University,School of AI and Advanced Computing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sihan","family":"Zhai","sequence":"additional","affiliation":[{"name":"Xi&#x2019;an Jiaotong-Liverpool University,School of AI and Advanced Computing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoqun","family":"Wang","sequence":"additional","affiliation":[{"name":"Xi&#x2019;an Jiaotong-Liverpool University,School of AI and Advanced Computing"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2196\/60077"},{"issue":"6","key":"ref2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3554729","article-title":"Deep EHR: A survey of recent advances in deep learning techniques for electronic health record (EHR) analysis","volume":"55","author":"Yang","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"ref3","volume-title":"Time Series Analysis: Forecasting and Control.","author":"Box","year":"1976"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.2307\/1912017"},{"key":"ref5","first-page":"253","article-title":"Modeling missing data in clinical time series with RNNs","volume-title":"Proc. 33rd Int. Conf. Mach. Learn. (ICML)","author":"Lipton"},{"key":"ref6","first-page":"787","article-title":"GRAM: Graph-based attention model for healthcare representation learning","volume-title":"Proc. 22nd ACM SIGKDD Int. Conf. Knowl. Discov. Data Min. (KDD)","author":"Choi"},{"key":"ref7","first-page":"301","article-title":"Doctor AI: Predicting clinical events via recurrent neural networks","volume-title":"Proc. 1st Mach. Learn. Healthcare Conf. (MLHC)","author":"Choi"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097997"},{"key":"ref9","first-page":"3504","article-title":"RETAIN: An interpretable predictive model for healthcare using reverse time attention mechanism","volume-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)","author":"Choi"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2009.2014565"},{"issue":"1","key":"ref11","first-page":"46","article-title":"Real-time forecasting of COVID-19 bed occupancy in wards and intensive care units","volume":"13","author":"Baas","year":"2024","journal-title":"Health Syst."},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0316-z"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-24271-9"},{"key":"ref14","first-page":"5679","article-title":"Interpolation-prediction networks for irregularly sampled time series","volume-title":"Proc. 36th Int. Conf. Mach. Learn. (ICML)","author":"Shukla"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1038\/srep26094"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939823"},{"key":"ref17","first-page":"5320","article-title":"Latent ODEs for irregularly-sampled time series","volume-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)","author":"Rubanova"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-018-0029-1"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783365"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3562095"}],"event":{"name":"ICC 2026 - IEEE International Conference on Communications","location":"Glasgow, United Kingdom","start":{"date-parts":[[2026,5,24]]},"end":{"date-parts":[[2026,5,28]]}},"container-title":["ICC 2026 - IEEE International Conference on Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11586754\/11586037\/11588033.pdf?arnumber=11588033","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T06:40:30Z","timestamp":1784097630000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11588033\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,24]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/icc59461.2026.11588033","relation":{},"subject":[],"published":{"date-parts":[[2026,5,24]]}}}