{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:46:41Z","timestamp":1762508801964},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"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":[[2022,5,25]]},"abstract":"<jats:p>Alarms help to detect medical conditions in intensive care units and improve patient safety. However, up to 99% of alarms are non-actionable, i.e. alarm that did not trigger a medical intervention in a defined time frame. Reducing their amount through machine learning (ML) is hypothesized to be a promising approach to improve patient monitoring and alarm management. This retrospective study presents the technical and medical pre-processing steps to annotate alarms into actionable and non-actionable, creating a basis for ML applications.<\/jats:p>","DOI":"10.3233\/shti220453","type":"book-chapter","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:13:43Z","timestamp":1653480823000},"source":"Crossref","is-referenced-by-count":3,"title":["Utilizing Intensive Care Alarms for Machine Learning"],"prefix":"10.3233","author":[{"given":"Anne Rike","family":"Flint","sequence":"first","affiliation":[{"name":"Institute of Medical Informatics, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sophie A.I.","family":"Klopfenstein","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"},{"name":"Berlin Institute of Health, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Heeren","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felix","family":"Balzer","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akira-Sebastian","family":"Poncette","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Challenges of Trustable AI and Added-Value on Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:13:43Z","timestamp":1653480823000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220453","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,25]]}}}