Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models.
Journal:
PloS one
Published Date:
Aug 20, 2025
Abstract
BACKGROUND: Lymphoma is a severe condition with high mortality rates, often requiring ICU admission. Traditional risk stratification tools like SOFA and APACHE scores struggle to capture complex clinical interactions. Machine learning (ML) models offer a more accurate alternative for predicting outcomes by analyzing large datasets. However, their application in predicting in-hospital mortality for lymphoma patients remains limited.
