Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models

Machine learning models, particularly the CatBoost Classifier, effectively predict in-hospital mortality in ICU patients with lymphoma. These models outperform traditional statistical methods and provide valuable insights into risk stratification. Future work should focus on external validation and clinical implementation to improve patient outcomes in this high-risk population.