{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:04:03Z","timestamp":1755219843134,"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>Mechanical ventilation weaning is critical for ICU patients, as prolonged or premature use can cause adverse outcomes and resource waste. Using six years of ICU data, Chi Mei Medical Center developed two-stage AI predictive models to optimize the timing for \u201cTrying Weaning\u201d and \u201cActual Weaning.\u201d The original Chi Mei models compared to external validation at Kaohsiung Medical University Hospital demonstrated AUCs of 0.981 vs. 0.915 for \u201cTrying Weaning\u201d and 0.915 vs. 0.866 for \u201cActual Weaning.\u201d The findings demonstrate that AI-assisted tools, supported by strong external validation results, can effectively reduce ventilation time, complications, and costs. Future research will focus on model optimization and multi-center validation.<\/jats:p>","DOI":"10.3233\/shti251010","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:38:04Z","timestamp":1754566684000},"source":"Crossref","is-referenced-by-count":0,"title":["From Internal Validation to External Validation: An Artificial Intelligence-Based Study on Predicting Optimal Timing for Mechanical Ventilation Weaning in ICU Patients"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6698-0273","authenticated-orcid":false,"given":"Chung-Feng","family":"Liu","sequence":"first","affiliation":[{"name":"Intelligent Healthcare Center, Chi Mei Medical Center, Tainan, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chin-Ming","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, Chi Mei Medical Center, Tainan, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3621-3334","authenticated-orcid":false,"given":"Ming-Ju","family":"Tsai","sequence":"additional","affiliation":[{"name":"Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhih-Cherng","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Chi Mei Medical Center, Tainan, Taiwan"}],"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\/SHTI251010","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:38:05Z","timestamp":1754566685000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251010"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251010","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]]}}}