Machine Learning–Based Prediction of Subsyndromal Delirium in Intensive Care Patients

Four machine learning-based risk prediction models and 1 traditional logistic regression model were developed to predict risk of subsyndromal delirium in ICU patients. Choosing a suitable model for early screening of ICU patients at high risk of subsyndromal delirium would allow medical staff to formulate individualized early intervention plans, which could improve patients' prognosis and save medical costs.