{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:04:44Z","timestamp":1755219884630,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"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":[[2025,8,7]]},"abstract":"<jats:p>We developed a novel model for cardiac arrest prediction using ICU data from SNUH and externally validated it on PNUYH. Our sequence-based embedding approach with a Mamba encoder outperformed NEWS and LightGBM, achieving AUROC 0.957 (internal) and 0.889 (external). This study highlights the potential of the proposed model as a robust and generalizable tool for early ICU intervention.<\/jats:p>","DOI":"10.3233\/shti251205","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:44:26Z","timestamp":1754567066000},"source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Cardiac Arrest Prediction in Critically Ill Patients: A Sequence-Based Embedding Approach with Mamba"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-8100-7110","authenticated-orcid":false,"given":"Ukdong","family":"Gim","sequence":"first","affiliation":[{"name":"VUNO Inc., Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunseob","family":"Shin","sequence":"additional","affiliation":[{"name":"VUNO Inc., Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongjoon","family":"Yoo","sequence":"additional","affiliation":[{"name":"VUNO Inc., Republic of Korea"},{"name":"Department of Critical Care Medicine and Emergency Medicine, Inha University College of Medicine, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyungjae","family":"Cho","sequence":"additional","affiliation":[{"name":"VUNO Inc., Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyung-Chul","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leerang","family":"Lim","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Woo Hyun","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Pulmonology, Allergy and Critical Care Medicine, Pusan National University Yangsan Hospital, Republic Of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251205","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:44:27Z","timestamp":1754567067000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251205"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251205","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}