Interpretable machine learning models based on shear‐wave elastography radiomics for predicting cardiovascular disease in diabetic kidney disease patients

This study highlights the effectiveness of an SVM model that combines clinical and radiomics features in predicting CVD risk among DKD patients. It enables early prediction of CVD in this patient group, thereby supporting the implementation of timely and suitable interventions.