Interpretable machine learning for predicting risk of invasive fungal infection in critically ill patients in the intensive care unit: A retrospective cohort study based on MIMIC-IV database.

Invasive fungal infections are characterized by high incidence and high mortality rates characteristics. In this study, we developed a clinical prediction model for invasive fungal infections in critically ill patients based on machine learning algorithms. The results show that the machine learning model based on 20 clinical features has good predictive value.