Predicting Early Recurrence of Hepatocellular Carcinoma in Cirrhotic Patients Post-Hepatectomy

Radiomics and clinical-radiologic features were integrated to develop a machine learning model for predicting early recurrence of hepatocellular carcinoma in cirrhotic patients post-hepatectomy. The model showed excellent predictive performance, with an AUC of 0.844 in the training cohort and 0.790 in the validation cohort, facilitating risk stratification and exhibiting significant discriminatory ability for overall survival.