Machine learning-based risk of pulmonary embolism in stroke patients with lower extremity deep vein thrombosis construction and validation of a prediction model

In this study, five machine learning models were established to assess the likelihood of pulmonary embolism in stroke patients with lower extremity deep vein thrombosis, among which the RFC model performed the best. We can promptly recognize and assess patients at risk of PE based on their SHAP, take early preventive and therapeutic measures, and improve the prognosis of patients.