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

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.

Detalles Bibliográficos

Principais autores:	Mingzhen Chen, Chunli Kong, Enqi Qiao, Yaning Chen, Weiyue Chen, Xiaole Jiang, Shiji Fang, Dengke Zhang, Minjiang Chen, Weiqian Chen, Jiansong Ji
Formato:	Artigo
Idioma:	Inglês
Publicado:	SpringerOpen 2023-02-01
Series:	Insights into Imaging
Assuntos:	Hepatocellular carcinoma Transarterial chemoembolization Deep learning Radiomics
Acceso en liña:	https://doi.org/10.1186/s13244-023-01380-2
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