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.

التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Mingzhen Chen, Chunli Kong, Enqi Qiao, Yaning Chen, Weiyue Chen, Xiaole Jiang, Shiji Fang, Dengke Zhang, Minjiang Chen, Weiqian Chen, Jiansong Ji
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	SpringerOpen 2023-02-01
سلاسل:	Insights into Imaging
الموضوعات:	Hepatocellular carcinoma Transarterial chemoembolization Deep learning Radiomics
الوصول للمادة أونلاين:	https://doi.org/10.1186/s13244-023-01380-2
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!