Understanding the risk factors for hepatocellular carcinoma (HCC) rupture can improve surgical outcomes.

• Key risk factors include cirrhosis, protrusion ratio, and maximum tumor length.
• The new capture nomogram achieved AUC values of 0.857, 0.824, and 0.840 across training, validation, and test groups, indicating high predictive accuracy.

Using these models can enhance early risk assessment and guide better management strategies for HCC patients, potentially reducing serious complications during surgery.

• Random forest and deep learning models reached even higher AUCs of 0.870 and 0.872 in the test cohort.