{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T10:00:11Z","timestamp":1747216811062,"version":"3.40.5"},"reference-count":0,"publisher":"University of Florida George A Smathers Libraries","issue":"1","license":[{"start":{"date-parts":[[2021,4,18]],"date-time":"2021-04-18T00:00:00Z","timestamp":1618704000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["FLAIRS"],"abstract":"<jats:p>In France, structured data from emergency room (ER) visits are aggregated at the national level to build a syndromic surveillance system for several health events. For visits motivated by a traumatic event, information on the causes are stored in free-text clinical notes. To exploit these data, an automated de-identification system guaranteeing protection of privacy is required.In this study we review available de-identification tools to de-identify free-text clinical documents in French.\u00a0A key point is how to overcome the resource barrier\u00a0that hampers NLP applications in languages other than\u00a0English. We compare rule-based, named entity recognition, new Transformer-based deep learning and hybrid systems using, when required, a fine-tuning set of 30,000 unlabeled clinical notes. The evaluation is performed on a test set of 3,000 manually annotated notes.Hybrid systems, combining capabilities in complementary tasks, show the best performance. This work is a first step in the foundation of a national surveillance system based on the exhaustive collection of ER visits reports for automated trauma monitoring.<\/jats:p>","DOI":"10.32473\/flairs.v34i1.128480","type":"journal-article","created":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T13:23:48Z","timestamp":1620912228000},"source":"Crossref","is-referenced-by-count":3,"title":["De-identification of Emergency Medical Records in French: Survey and Comparison of State-of-the-Art Automated Systems"],"prefix":"10.32473","volume":"34","author":[{"given":"Loick","family":"Bourdois","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5471-2615","authenticated-orcid":false,"given":"Marta","family":"Avalos","sequence":"first","affiliation":[]},{"given":"Gabrielle","family":"Chenais","sequence":"first","affiliation":[]},{"given":"Frantz","family":"Thiessard","sequence":"first","affiliation":[]},{"given":"Philippe","family":"Revel","sequence":"first","affiliation":[]},{"given":"Cedric","family":"Gil-Jardine","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8031-7400","authenticated-orcid":false,"given":"Emmanuel","family":"Lagarde","sequence":"first","affiliation":[]}],"member":"17357","published-online":{"date-parts":[[2021,4,18]]},"container-title":["The International FLAIRS Conference Proceedings"],"original-title":[],"link":[{"URL":"https:\/\/journals.flvc.org\/FLAIRS\/article\/download\/128480\/130075","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.flvc.org\/FLAIRS\/article\/download\/128480\/130075","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T13:25:01Z","timestamp":1620912301000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.flvc.org\/FLAIRS\/article\/view\/128480"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,18]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,5,11]]}},"URL":"https:\/\/doi.org\/10.32473\/flairs.v34i1.128480","relation":{},"ISSN":["2334-0762"],"issn-type":[{"type":"print","value":"2334-0762"}],"subject":[],"published":{"date-parts":[[2021,4,18]]}}}