Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI

Abstract

Key points DNN and LASSO models performed better than other classifiers in TACE response prediction. CD model achieved an AUC of 0.974 in the training set, superior to other comprehensive models. CD model may serve as a potential tool for the selection of suitable TACE candidates.

Keywords

• Hepatocellular carcinoma
• Transarterial chemoembolization
• Deep learning
• Radiomics