Article

Improving mortality prediction in critically ill cancer patients with a multidimensional machine learning model

2026-02-03

Abstract excerpt

<h4>Background</h4> Prognostic assessment in critically ill patients with cancer remains challenging, as conventional ICU severity scores often perform suboptimally in this population. Machine learning (ML) approaches may improve outcome prediction by integrating acute physiology, organ dysfunction, and oncologic variables. We aimed to develop and validate ML-based models to predict ICU mortality and 30-day survi...

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Literature Corpus work: 215bb961-e249-5424-ab80-afab53502072
DOI: 10.64898/2026.02.02.26345349

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