{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T12:22:21Z","timestamp":1754396541365,"version":"3.28.0"},"reference-count":66,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"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":[[2020,12,10]]},"DOI":"10.1109\/bigdata50022.2020.9377829","type":"proceedings-article","created":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T17:10:21Z","timestamp":1616173821000},"page":"1246-1255","source":"Crossref","is-referenced-by-count":3,"title":["MuLan: Multilevel Language-based Representation Learning for Disease Progression Modeling"],"prefix":"10.1109","author":[{"given":"Hyunwoo","family":"Sohn","sequence":"first","affiliation":[]},{"given":"Kyungjin","family":"Park","sequence":"additional","affiliation":[]},{"given":"Min","family":"Chi","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9006002"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2016.45"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.aab3719"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201209-1726OC"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1177\/0885066610392499"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219885"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788627"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2875677"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1080\/00437956.1954.11659520"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/322"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1186\/s13613-019-0498-7"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.4304\/jcp.1.3.51-60"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000001087"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s00134-007-0934-2"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.21037\/jtd.2016.05.55"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2018.7571"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1111\/imj.14199"},{"key":"ref66","first-page":"2579","article-title":"Visualizing data using t-sne","volume":"9","author":"maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1097\/01.CCM.0000217961.75225.E9"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783365"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/clpt.2012.53"},{"key":"ref20","first-page":"1188","article-title":"Distributed representations of sentences and documents","author":"le","year":"2014","journal-title":"ICML"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109890"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858759"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2018.06.016"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1378\/chest.101.6.1644"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2633963"},{"key":"ref50","first-page":"65","article-title":"Paient subtyping via time-aware lstm networks","author":"baytas","year":"2017","journal-title":"SIGKDD"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783352"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1001\/archsurg.133.11.1200"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.12669\/pjms.315.6925"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0287"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.4037\/ajcc2007.16.2.122"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339578"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622436"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-24271-9"},{"key":"ref52","first-page":"1665","article-title":"A multi-task framework for monitoring health conditions via attention-based recurrent neural networks","author":"suo","year":"2017","journal-title":"AMIA"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-publhealth-031914-122747"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI.2016.16"},{"key":"ref40","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"NeurIPS"},{"article-title":"Learning to diagnose with lstm recurrent neural networks","year":"2015","author":"lipton","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020549"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.49"},{"key":"ref15","first-page":"440","article-title":"Deep ehr: Chronic disease prediction using medical notes","author":"liu","year":"2018","journal-title":"MLHC"},{"key":"ref16","first-page":"73","article-title":"Multi-task prediction of disease onsets from longitudinal laboratory tests","author":"razavian","year":"2016","journal-title":"MLHC"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8621927"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI.2018.00032"},{"key":"ref19","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"2013","journal-title":"NeurIPS"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939823"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2110363.2110408"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972832.7"},{"key":"ref5","first-page":"301","article-title":"Doctor ai: Predicting clinical events via recurrent neural networks","author":"choi","year":"2016","journal-title":"MLHC"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098126"},{"key":"ref7","first-page":"3504","article-title":"Retain: An interpretable predictive model for healthcare using reverse time attention mechanism","author":"choi","year":"2016","journal-title":"NeurIPS"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623754"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2808719.2808741"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM47256.2019.8983281"},{"article-title":"Attend and diagnose: Clinical time series analysis using attention models","year":"2017","author":"song","key":"ref45"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.144"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258049"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1609\/aaai.v34i01.5428","article-title":"Concare: Personalized clinical feature embedding via capturing the healthcare context","volume":"34","author":"ma","year":"2020","journal-title":"AAAI"},{"article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","year":"2018","author":"devlin","key":"ref41"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2984931"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-62922-y"}],"event":{"name":"2020 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2020,12,10]]},"location":"Atlanta, GA, USA","end":{"date-parts":[[2020,12,13]]}},"container-title":["2020 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9377717\/9377728\/09377829.pdf?arnumber=9377829","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T11:42:58Z","timestamp":1656330178000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9377829\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,10]]},"references-count":66,"URL":"https:\/\/doi.org\/10.1109\/bigdata50022.2020.9377829","relation":{},"subject":[],"published":{"date-parts":[[2020,12,10]]}}}