Defining a radiomics feature selection method for predicting response to transarterial chemoembolization in hepatocellular carcinoma patients

Aim: To assess the utility of different radiomics feature selection methods in predicting transarterial chemoembolization (TACE) response in hepatocellular carcinoma (HCC) patients. Materials and methods: This study employed a dataset of 136 paired MR T1-weighted contrast-enhanced abdominal images w...

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Bibliografische gegevens

Hoofdauteurs:	Helen Zhang, Li Yang, Amanda Laguna, Jing Wu, Beiji Zou, Alireza Mohseni, Rajat S. Chandra, Tej I. Mehta, Hossam A. Zaki, Paul Zhang, Zhicheng Jiao, Ihab R. Kamel, Harrison X. Bai
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	KeAi Communications Co., Ltd. 2024-03-01
Reeks:	Meta-Radiology
Onderwerpen:	Radiomics Feature selection Machine learning Hepatocellular carcinoma Transarterial chemoembolization
Online toegang:	http://www.sciencedirect.com/science/article/pii/S2950162824000201
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