{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T09:41:44Z","timestamp":1685612504163},"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>Context: We present a post-hoc approach to improve the recall of ICD classification. Method: The proposed method can use any classifier as a backbone and aims to calibrate the number of codes returned per document. We test our approach on a new stratified split of the MIMIC-III dataset. Results: When returning 18 codes on average per document we obtain a recall that is 20% better than a classic classification approach.<\/jats:p>","DOI":"10.3233\/shti230264","type":"book-chapter","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T08:47:13Z","timestamp":1684486033000},"source":"Crossref","is-referenced-by-count":0,"title":["Learning to Classify Medical Discharge Summaries According to ICD-9"],"prefix":"10.3233","author":[{"given":"Leonardo","family":"Moros","sequence":"first","affiliation":[{"name":"LIRMM UMR 5506, University of Montpellier, CNRS, Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00e9r\u00f4me","family":"Az\u00e9","sequence":"additional","affiliation":[{"name":"LIRMM UMR 5506, University of Montpellier, CNRS, Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandra","family":"Bringay","sequence":"additional","affiliation":[{"name":"LIRMM UMR 5506, University of Montpellier, CNRS, Montpellier, France"},{"name":"AMIS, Paul-Val\u00e9ry University, Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Poncelet","sequence":"additional","affiliation":[{"name":"LIRMM UMR 5506, University of Montpellier, CNRS, Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maximilien","family":"Servajean","sequence":"additional","affiliation":[{"name":"LIRMM UMR 5506, University of Montpellier, CNRS, Montpellier, France"},{"name":"AMIS, Paul-Val\u00e9ry University, Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caroline","family":"Dunoyer","sequence":"additional","affiliation":[{"name":"Medical Information Department, CHU Montpellier, Montpellier, France"},{"name":"IDESP, UMR UA11, INSERM \u2013 University of Montpellier, Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"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\/SHTI230264","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T15:01:28Z","timestamp":1685545288000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230264"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"ISBN":["9781643683881","9781643683898"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230264","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]]}}}