{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,19]],"date-time":"2024-04-19T18:09:24Z","timestamp":1713550164158},"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>Outcome prediction in wake-up ischemic stroke (WUS) is important for guiding treatment strategies, in order to improve recovery and minimize disability. We aimed at producing an interpretable model to predict a good outcome (NIHSS 7-day&lt;5) in thrombolysis treated WUS patients by using Classification and Regression Tree (CART) method. The study encompassed 104 WUS patients and we used a dataset consisting of demographic, clinical and neuroimaging features. The model was produced by CART with Gini split criterion and evaluated by using 5-fold cross-validation. The produced decision tree model was based on NIHSS at admission, ischemic core volume and age features. The predictive accuracy of model was 86.5% and the AUC-ROC was 0.88. In conclusion, in this preliminary study we identified interpretable model based on clinical and neuroimaging features to predict clinical outcome in thrombolysis treated wake-up stroke patients.<\/jats:p>","DOI":"10.3233\/shti220527","type":"book-chapter","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:15:53Z","timestamp":1653480953000},"source":"Crossref","is-referenced-by-count":2,"title":["Wake-up Stroke Outcome Prediction by Interpretable Decision Tree Model"],"prefix":"10.3233","author":[{"given":"Milo\u0161","family":"Aj\u010devi\u0107","sequence":"first","affiliation":[{"name":"Department of Engineering and Architecture, University of Trieste, Trieste, Italy"}]},{"given":"Aleksandar","family":"Miladinovi\u0107","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture, University of Trieste, Trieste, Italy"}]},{"given":"Giovanni","family":"Furlanis","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Science, University of Trieste, Trieste, Italy"}]},{"given":"Alex","family":"Buoite Stella","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Science, University of Trieste, Trieste, Italy"}]},{"given":"Marcello","family":"Naccarato","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Science, University of Trieste, Trieste, Italy"}]},{"given":"Paola","family":"Caruso","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Science, University of Trieste, Trieste, Italy"}]},{"given":"Paolo","family":"Manganotti","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Science, University of Trieste, Trieste, Italy"}]},{"given":"Agostino","family":"Accardo","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture, University of Trieste, Trieste, Italy"}]}],"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\/SHTI220527","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:15:54Z","timestamp":1653480954000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220527"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220527","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]]}}}