Kamil Adamczyk

Abstract Accurate prognostication in the intensive care unit (ICU) is essential for delivering personalized and ethically sound care, yet it remains a challenge for high-risk patients. This study aimed to develop and validate an exploratory machine learning model for predicting ICU mortality in critically ill patients requiring both mechanical ventilation and vasoactive support. We conducted a retrospective analysis of 4816 patient records from the AmsterdamUMCdb database.

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All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.