{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:05:08Z","timestamp":1787025908841,"version":"build-2736575974"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686615","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"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":[[2026,5,21]]},"abstract":"<jats:p>Accurate prediction of early functional outcome after acute ischemic stroke is critical for clinical decision-making. This retrospective cohort study developed and externally validated a machine learning model using routine clinical data from two settings. A total of 11,911 ischemic patients from the 2023 Stroke Care Quality (RES-Q) registry in 52 hospitals across Vietnam and 83 patients from UGM Academic Hospital, Indonesia, were included. The primary outcome was discharge modified Rankin Scale (mRS\u22642=favorable; &gt;2 = poor). The XGBoost model achieved strong internal discrimination (AUC=0.905, F1=0.836) and maintained robust external performance (AUC=0.888, F1=0.810). SHAP interpretability identified pre-stroke mRS, admission NIHSS score, first-day glucose check, and age as the strongest predictors of poor functional outcome, while early dysphagia screening, physiotherapy evaluation, and small-vessel etiology were associated with better recovery. These results demonstrate that a data-driven AI approach using routine clinical parameters can achieve reliable cross-regional generalization and may support early prognostication in diverse stroke care settings.<\/jats:p>","DOI":"10.3233\/shti260140","type":"book-chapter","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:56:24Z","timestamp":1779400584000},"source":"Crossref","is-referenced-by-count":1,"title":["Prediction of Early Functional Outcome After Acute Ischemic Stroke Using Real-World Clinical Data in Vietnam and Indonesia: Retrospective Cohort Study"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9478-6267","authenticated-orcid":false,"given":"Annisa Ristya","family":"Rahmanti","sequence":"first","affiliation":[{"name":"Department of Health Policy and Management, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia"},{"name":"London Digital Twin Research Center, Middlesex University, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lutfan","family":"Lazuardi","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cong Minh","family":"Tran","sequence":"additional","affiliation":[{"name":"Nuffield Department of Medicine, University of Oxford, United Kingdom; School of Computing and Mathematical Sciences, University of Leicester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanifah","family":"Wulandari","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ika Agustin A.","family":"Putri","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farida Niken A.N.","family":"Hati","sequence":"additional","affiliation":[{"name":"UGM Academic Hospital, Yogyakarta, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7210-3522","authenticated-orcid":false,"given":"Mai Duy","family":"Ton","sequence":"additional","affiliation":[{"name":"Stroke Center, Bach Mai Hospital; Hanoi Medical University; VNU-University of Medicine and Pharmacy, Hanoi, Viet Nam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4105-2558","authenticated-orcid":false,"given":"Huan X.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"London Digital Twin Research Center, Middlesex University, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Opening the Personal Gate between Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260140","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:56:24Z","timestamp":1779400584000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260140"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,21]]},"ISBN":["9781643686615"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260140","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,21]]}}}