{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:04:51Z","timestamp":1755219891691,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643686080"}],"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>This study mapped K-MIMIC (Korean Medical Information Mart for Intensive Care) nursing data to SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms), an international standard terminology, to assess its potential for data standardization and utilization in AI (Artificial Intelligence)-based CDSS (Clinical Decision Support System) development. Of approximately 12,000 nursing data entries from two hospitals, 8,424 were included in the final mapping, with exact matches accounting for 90.4%, broad matches for 8.5%, and unmatched entries for 1.1%. Additionally, 76.9% of the data were classified as 1:N mappings, with the primary categories being Procedures (57.1%) and Clinical findings (38.2%). The results confirm that SNOMED CT is suitable for representing intensive care nursing data, supporting AI development and clinical decision-making. This study highlights the importance of standardizing and optimizing nursing data for CDSS development and suggests that future research should focus on improving the mapping process and validating the effectiveness of CDSS based on standardized data.<\/jats:p>","DOI":"10.3233\/shti250799","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:31:27Z","timestamp":1754566287000},"source":"Crossref","is-referenced-by-count":0,"title":["Optimizing Nursing Data for Al and CDSS: SNOMED CT Mapping Using K-MIMIC"],"prefix":"10.3233","author":[{"given":"Youngeun","family":"Kim","sequence":"first","affiliation":[{"name":"WITH LAB, Gangneung-Wonju National University, Wonju, Gangwon state, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"IMPACT consortium","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mijeong","family":"Park","sequence":"additional","affiliation":[{"name":"WITH LAB, Gangneung-Wonju National University, Wonju, Gangwon state, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang-Min","family":"Lee","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ho Geol","family":"Ryu","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyung-Chul","family":"Lee","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taehoon","family":"Ko","sequence":"additional","affiliation":[{"name":"The Catholic University of Korea, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jongho","family":"Shin","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sul Mui","family":"Won","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sae Won","family":"Choi","sequence":"additional","affiliation":[{"name":"Veterans Health Service Medical Center, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Young-Gon","family":"Kim","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eui Kyu","family":"Chie","sequence":"additional","affiliation":[{"name":"Seoul National University Hospital, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jisan","family":"Lee","sequence":"additional","affiliation":[{"name":"WITH LAB, Gangneung-Wonju National University, Wonju, Gangwon state, 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\/SHTI250799","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:31:28Z","timestamp":1754566288000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250799","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}