An interpretable machine learning model based on contrast-enhanced CT parameters for predicting treatment response to conventional transarterial chemoembolization in patients with hepatocellular carcinoma-Reference-Cited by-同舟云学术

An interpretable machine learning model based on contrast-enhanced CT parameters for predicting treatment response to conventional transarterial chemoembolization in patients with hepatocellular carcinoma

Published:2024-02-14 Issue:3 Volume:129 Page:353-367
ISSN:1826-6983
Container-title:La radiologia medica
language:en
Short-container-title:Radiol med

Author:

Zhang Lu,Jin Zhe,Li Chen,He Zicong,Zhang Bin,Chen Qiuying,You Jingjing,Ma Xiao,Shen Hui,Wang Fei,Wu Lingeng,Ma Cunwen,Zhang Shuixing^ORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Science and Technology Projects in Guangzhou

Postdoctoral Research Foundation of China

Clinical Frontier Technology Program of the First Affiliated Hospital of Jinan University

Science and Technology Youth Talent Nurturing Program of Jinan University

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11547-024-01785-z.pdf

Reference34 articles.

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