{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:34:23Z","timestamp":1740202463614,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009]]},"abstract":"<jats:p>This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes according to the time they need to reach a stable state after coronary bypass surgery: less or more than nine hours. On the basis of five physiological variables different dynamic features were extracted. These sets of features served subsequently as inputs for a Gaussian process and the prediction results were compared with the case where only admission data was used for the classification. The dynamic features, especially the cepstral coefficients (aROC: 0.749, Brier score: 0.206), resulted in higher performances when compared to static admission data (aROC: 0.547, Brier score: 0.247). In all cases, the Gaussian process classifier outperformed logistic regression.<\/jats:p>","DOI":"10.3233\/978-1-60750-044-5-590","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:45:24Z","timestamp":1740149124000},"source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability"],"prefix":"10.3233","author":[{"family":"Van Loon Kristien","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Guiza Fabian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Meyfroidt Geert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Aerts Jean-Marie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ramon Jan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Blockeel Hendrik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Bruynooghe Maurice","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Van Den Berghe Greet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Berckmans Daniel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Medical Informatics in a United and Healthy Europe"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T15:44:46Z","timestamp":1740152686000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0926-9630&volume=150&spage=590"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-60750-044-5-590","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2009]]}}}