Development and validation of a machine learning model for predicting preoperative deep vein thrombosis in elderly hip fracture patients

The XGBoost-based predictive model for preoperative DVT in elderly patients with hip fractures demonstrated superior performance. By integrating the SHAP method to enhance model interpretability and developing an intuitive web-based tool, the model's clinical applicability was markedly improved. This predictive tool holds promise for assisting clinicians in risk assessment and guiding medical decision-making.