{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T04:48:11Z","timestamp":1751690891722,"version":"3.28.0"},"reference-count":78,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T00:00:00Z","timestamp":1696809600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T00:00:00Z","timestamp":1696809600000},"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":[[2023,10,9]]},"DOI":"10.1109\/dsaa60987.2023.10302556","type":"proceedings-article","created":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T19:07:21Z","timestamp":1699297641000},"page":"1-10","source":"Crossref","is-referenced-by-count":3,"title":["Leveraging patient similarities via graph neural networks to predict phenotypes from temporal data"],"prefix":"10.1109","author":[{"given":"Dimitrios","family":"Proios","sequence":"first","affiliation":[{"name":"University of Geneva,Geneva,Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anthony","family":"Yazdani","sequence":"additional","affiliation":[{"name":"University of Geneva,Geneva,Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alban","family":"Bornet","sequence":"additional","affiliation":[{"name":"University of Geneva,Geneva,Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julien","family":"Ehrsam","sequence":"additional","affiliation":[{"name":"University of Geneva &#x0026; Geneva University Hospitals,Geneva,Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Islem","family":"Rekik","sequence":"additional","affiliation":[{"name":"Imperial College London,London,UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Douglas","family":"Teodoro","sequence":"additional","affiliation":[{"name":"University of Geneva,Geneva,Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103671"},{"key":"ref57","first-page":"1","article-title":"Understanding cancer complexome using networks, spectral graph theory and multilayer framework","volume":"7","author":"rai","year":"2017","journal-title":"Scientific Reports"},{"key":"ref12","first-page":"2023","article-title":"Comparing neural language models for medical concept representation and patient trajectory prediction","author":"bornet","year":"2023","journal-title":"medRxiv"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103426"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2017.2767063"},{"key":"ref59","doi-asserted-by":"crossref","first-page":"5858","DOI":"10.1038\/s41598-021-85255-w","article-title":"Leveraging graph-based hierarchical medical entity embedding for healthcare applications","volume":"11","author":"wu","year":"2021","journal-title":"Scientific Reports"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IISA.2018.8633647"},{"key":"ref58","article-title":"Efficient representation learning using random walks for dynamic graphs","author":"sajjad","year":"2019","journal-title":"arXiv preprint arXiv 1901 01023"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/BHI50953.2021.9508558"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"19892e","DOI":"10.2196\/19892","article-title":"Decompensation in critical care: early prediction of acute heart failure onset","volume":"8","author":"balkan","year":"2020","journal-title":"JMIR Medical Informatics"},{"key":"ref11","first-page":"2023","article-title":"Detection of patients at risk of enterobacteriaceae infection using graph neural networks: a retrospective study","author":"gouareb","year":"2023","journal-title":"medRxiv"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2018.08.029"},{"journal-title":"Cluster Analysis of Low-Dimensional Medical Concept Representations from Electronic Health Records","year":"2022","key":"ref10"},{"key":"ref54","article-title":"Clinicalbert: Modeling clinical notes and predicting hospital readmission","author":"huang","year":"2019","journal-title":"arXiv preprint arXiv 1904 05342"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0192360"},{"article-title":"Phe2vec: automated disease phenotyping based on unsupervised embeddings from electronic health records. patterns 2 (9), 100337 (2021)","year":"2021","author":"de freitas","key":"ref16"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-020-0301-z"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2013-001935"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/SIEDS.2018.8374719"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1142\/9789811215636_0010"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.3390\/app122211709"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/2188\/1\/012007"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2020.06.008"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.21236\/ADA164453"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271701"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098126"},{"key":"ref44","article-title":"Dig: A turnkey library for diving into graph deep learning research","volume":"22","author":"liu","year":"2021","journal-title":"J Mach Learn Res"},{"article-title":"Cogdl: A toolkit for deep learning on graphs","year":"2021","author":"cen","key":"ref43"},{"key":"ref49","first-page":"460","article-title":"An interpretable icu mortality prediction model based on logistic regression and recurrent neural networks with lstm units","volume":"2018","author":"ge","year":"2018","journal-title":"AMIA Annual Symposium Proceedings"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocac216"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbv083"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocv202"},{"key":"ref4","doi-asserted-by":"crossref","DOI":"10.4103\/ijpvm.IJPVM_375_19","article-title":"Precision medicine: A new paradigm in therapeutics","volume":"12","author":"akhoon","year":"2021","journal-title":"International Journal of Preventive Medicine"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-019-0103-9"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2022.842306"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8111235"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783352"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8488991"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-018-0029-1"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"kingma","key":"ref78"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00455-y"},{"key":"ref36","first-page":"41","article-title":"Learning low-dimensional representations of medical concepts","volume":"2016","author":"choi","year":"2016","journal-title":"AMIA Summits on Translational Science Proceedings"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103671"},{"article-title":"Two-stage training of graph neural networks for graph classification","year":"2020","author":"do","key":"ref75"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2019.103337"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330925"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.49"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783365"},{"article-title":"A survey and taxonomy of graph sampling","year":"2013","author":"hu","key":"ref76"},{"article-title":"MIMIC-III clinical database (version 1.4)","year":"2016","author":"johnson","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.35"},{"key":"ref39","first-page":"1","article-title":"Behrt: transformer for electronic health records","volume":"10","author":"li","year":"2020","journal-title":"Scientific Reports"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11635"},{"key":"ref71","article-title":"Inductive representation learning on large graphs","volume":"abs 1706 2216","author":"hamilton","year":"2017","journal-title":"CoRR"},{"year":"0","key":"ref70","article-title":"Statpearls - ncbi bookshelf"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0098679"},{"key":"ref72","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2013","journal-title":"2nd International Conference on Learning Representations ICLR 2014 - Conference Track Proceedings"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patter.2023.100689"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1162\/089976600300015015"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-09342-5_24"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-34239-7"},{"key":"ref26","article-title":"Graph convolutional transformer: Learning the graphical structure of electronic health records","volume":"abs 1906 4716","author":"choi","year":"2019","journal-title":"CoRR"},{"article-title":"Predicting patient outcomes with graph representation learning","year":"2021","author":"rocheteau","key":"ref25"},{"journal-title":"Computational Geometry An Introduction ser Monographs in Computer Science","year":"2012","author":"preparata","key":"ref69"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00097"},{"article-title":"Is homophily a necessity for graph neural networks?","year":"2021","author":"ma","key":"ref64"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539319"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.48"},{"article-title":"Semi-supervised classification with graph convolutional networks","year":"2017","author":"kipf","key":"ref66"},{"key":"ref21","first-page":"10 956","article-title":"Memorygated recurrent networks","volume":"12b","author":"zhang","year":"2020","journal-title":"35th AAAI Conference on Artificial Intelligence AAAI 2021"},{"key":"ref65","first-page":"5999","article-title":"Attention is all you need","volume":"2017 december","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3368555.3384469"},{"key":"ref27","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Advances in neural information processing systems"},{"year":"2019","key":"ref29","article-title":"International statistical classification of diseases and related health problems"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557108"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-020-01155-x"},{"article-title":"Learning representations of missing data for predicting patient outcomes","year":"2018","author":"malone","key":"ref61"}],"event":{"name":"2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)","start":{"date-parts":[[2023,10,9]]},"location":"Thessaloniki, Greece","end":{"date-parts":[[2023,10,13]]}},"container-title":["2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10302431\/10302461\/10302556.pdf?arnumber=10302556","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T13:37:22Z","timestamp":1730468242000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10302556\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,9]]},"references-count":78,"URL":"https:\/\/doi.org\/10.1109\/dsaa60987.2023.10302556","relation":{},"subject":[],"published":{"date-parts":[[2023,10,9]]}}}