{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T09:12:24Z","timestamp":1685610744283},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683881","type":"print"},{"value":"9781643683898","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,18]]},"abstract":"<jats:p>Machine learning methods are becoming increasingly popular to anticipate critical risks in patients under surveillance reducing the burden on caregivers. In this paper, we propose an original modeling that benefits of recent developments in Graph Convolutional Networks: a patient\u2019s journey is seen as a graph, where each node is an event and temporal proximities are represented by weighted directed edges. We evaluated this model to predict death at 24 hours on a real dataset and successfully compared our results with the state of the art.<\/jats:p>","DOI":"10.3233\/shti230205","type":"book-chapter","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T08:45:31Z","timestamp":1684485931000},"source":"Crossref","is-referenced-by-count":0,"title":["Patient Electronic Health Record as Temporal Graphs for Health Monitoring"],"prefix":"10.3233","author":[{"given":"Hugo","family":"Le Baher","sequence":"first","affiliation":[{"name":"LIRMM, UMR 5506, Universit\u00e9 de Montpellier, CNRS, Montpellier, France"},{"name":"5 DEGR\u00c9S, Paris, France"},{"name":"D\u00e9partement d\u2019Information M\u00e9dicale, CHU Montpellier, Montpellier, France"}]},{"given":"J\u00e9r\u00f4me","family":"Az\u00e9","sequence":"additional","affiliation":[{"name":"5 DEGR\u00c9S, Paris, France"}]},{"given":"Sandra","family":"Bringay","sequence":"additional","affiliation":[{"name":"LIRMM, UMR 5506, Universit\u00e9 de Montpellier, CNRS, Montpellier, France"},{"name":"AMIS, Universit\u00e9 Paul-Val\u00e9ry, Montpellier, France"}]},{"given":"Pascal","family":"Poncelet","sequence":"additional","affiliation":[{"name":"LIRMM, UMR 5506, Universit\u00e9 de Montpellier, CNRS, Montpellier, France"}]},{"given":"Nancy","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"LIRMM, UMR 5506, Universit\u00e9 de Montpellier, CNRS, Montpellier, France"}]},{"given":"Caroline","family":"Dunoyer","sequence":"additional","affiliation":[{"name":"D\u00e9partement d\u2019Information M\u00e9dicale, CHU Montpellier, Montpellier, France"},{"name":"IDESP, UMR UA11, INSERM \u2013 Universit\u00e9 de Montpellier, Montpellier, France"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Caring is Sharing \u2013 Exploiting the Value in Data for Health and Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230205","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T14:59:22Z","timestamp":1685545162000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230205"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"ISBN":["9781643683881","9781643683898"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230205","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,18]]}}}