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Although these simple additive models are human readable and interpretable, their predictive performance needs to be further improved.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We present OASIS\u2009+, a variant of the Oxford Acute Severity of Illness Score (OASIS) in which an ensemble of 200 decision trees is used to predict in-hospital mortality based on the 10 same clinical variables in OASIS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Using a test set of 9566 admissions extracted from the MIMIC-III database, we show that OASIS\u2009+\u2009outperforms nine previously developed severity scoring methods (including OASIS) in predicting in-hospital mortality. Furthermore, our results show that the supervised learning algorithms considered in our experiments demonstrated higher predictive performance when trained using the observed clinical variables as opposed to OASIS subscores.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our results suggest that there is room for improving the prognostic accuracy of the OASIS severity scores by replacing the simple linear additive scoring function with more sophisticated non-linear machine learning models such as RF and XGB.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12911-021-01517-7","type":"journal-article","created":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T14:03:03Z","timestamp":1620914583000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["OASIS\u2009+: leveraging machine learning to improve the prognostic accuracy of OASIS severity score for predicting in-hospital mortality"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4681-7994","authenticated-orcid":false,"given":"Yasser","family":"EL-Manzalawy","sequence":"first","affiliation":[]},{"given":"Mostafa","family":"Abbas","sequence":"additional","affiliation":[]},{"given":"Ian","family":"Hoaglund","sequence":"additional","affiliation":[]},{"given":"Alvaro Ulloa","family":"Cerna","sequence":"additional","affiliation":[]},{"given":"Thomas B.","family":"Morland","sequence":"additional","affiliation":[]},{"given":"Christopher M.","family":"Haggerty","sequence":"additional","affiliation":[]},{"given":"Eric S.","family":"Hall","sequence":"additional","affiliation":[]},{"given":"Brandon K.","family":"Fornwalt","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,5,13]]},"reference":[{"issue":"5","key":"1517_CR1","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1093\/bjaceaccp\/mkn033","volume":"8","author":"DC Bouch","year":"2008","unstructured":"Bouch DC, Thompson JP. 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