{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T07:59:12Z","timestamp":1730275152234,"version":"3.28.0"},"reference-count":26,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,3]]},"DOI":"10.1109\/ismict.2018.8573698","type":"proceedings-article","created":{"date-parts":[[2018,12,13]],"date-time":"2018-12-13T19:36:26Z","timestamp":1544729786000},"page":"1-6","source":"Crossref","is-referenced-by-count":3,"title":["Deep Holistic Representation Learning from EHR"],"prefix":"10.1109","author":[{"given":"Edmond","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reece","family":"Robinson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernhard","family":"Pfahringer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2633963"},{"journal-title":"Clinical Entity Recognition for ICD-9 Code Prediction in Clinical Discharge Summaries","year":"2017","author":"berlin","key":"ref11"},{"key":"ref12","article-title":"Automatic ICD Code Assignment to Medical Text with Semantic Relational Tuples","volume":"2","author":"zhao","year":"2017","journal-title":"Proceedings of the iConference 2017"},{"key":"ref13","article-title":"Supervised Topic Models for Diagnosis Code Assignment to Discharge Summaries","author":"dermouche","year":"2016","journal-title":"Proceedings of the 17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing16)"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3079452.3079498"},{"key":"ref15","first-page":"301","article-title":"Doctor ai: Predicting clinical events via recurrent neural networks","author":"choi","year":"2016","journal-title":"Machine Learning for Healthcare Conference"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI.2015.58"},{"key":"ref17","article-title":"Temp oral pattern and association discovery of diagnosis codes using deep learning","author":"saaed","year":"2015","journal-title":"Healthcare Informatics (ICHI) 2015 IEEE International Conference"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1082"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1056"},{"key":"ref4","article-title":"DeepCare: A Deep Dynamic Memory Model for Predictive Medicine","author":"pham","year":"2016","journal-title":"PAKDD"},{"journal-title":"Learning to diagnose with LSTM recurrent neural networks","year":"2015","author":"lipton","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-30671-1_66"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"26094","DOI":"10.1038\/srep26094","article-title":"Deep patient: An unsupervised representation to predict the future of patients from the electronic health records","volume":"6","author":"miotto","year":"2016","journal-title":"Scientific Reports"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/jhm.2568"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2017.04.001"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.49"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.12788\/jhm.2711"},{"key":"ref1","article-title":"Adoption of electronic health record systems among US non-federal acute care hospitals: 2008–2015","author":"henry","year":"2016","journal-title":"Report to the Office of the National Coordinator for Health Information Technology"},{"key":"ref20","first-page":"624","article-title":"Named entity recognition in Chinese clinical text using deep neural network","volume":"216","author":"wu","year":"2015","journal-title":"Studies in Health Technology and Informatics"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.01.012"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939823"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.35"},{"journal-title":"Multitask Learning and Benchmarking with Clinical Time Series Data","year":"2017","author":"harutyunyan","key":"ref26"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"}],"event":{"name":"2018 12th International Symposium on Medical Information and Communication Technology (ISMICT)","start":{"date-parts":[[2018,3,26]]},"location":"Sydney, NSW","end":{"date-parts":[[2018,3,28]]}},"container-title":["2018 12th International Symposium on Medical Information and Communication Technology (ISMICT)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8554188\/8573689\/08573698.pdf?arnumber=8573698","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T22:56:24Z","timestamp":1643237784000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8573698\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/ismict.2018.8573698","relation":{},"subject":[],"published":{"date-parts":[[2018,3]]}}}