Machine Learning-Based Prediction of In-Hospital Mortality in Patients with Pneumonic Chronic Obstructive Pulmonary Disease Exacerbations.

The RF model demonstrated superior predictive capabilities than the BAP-65 and CURB-65 models in predicting in-hospital mortality. The results further highlighted significant factors for predicting in-hospital mortality, including blood eosinophil count, systolic blood pressure, and prior history of asthma.