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Real-time automatic prediction of treatment response to transcatheter arterial chemoembolization in patients with hepatocellular carcinoma using deep learning based on digital subtraction angiography videos

Crossref DOI link: https://doi.org/10.1186/s40644-022-00457-3

Published Online: 2022-05-12

Published Print: 2022-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhang, Lu

Jiang, Yicheng

Jin, Zhe

Jiang, Wenting

Zhang, Bin

Wang, Changmiao

Wu, Lingeng

Chen, Luyan

Chen, Qiuying

Liu, Shuyi

You, Jingjing

Mo, Xiaokai

Liu, Jing

Xiong, Zhiyuan

Huang, Tao

Yang, Liyang

Wan, Xiang

Wen, Ge

Han, Xiao Guang

Fan, Weijun

Zhang, Shuixing https://orcid.org/0000-0001-7377-382X
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (81871323, 81801665, 81901709, 61931024)

Natural Science Foundation of Guangdong Province (2019A1515011918, 2019A1515111161)
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Text and Data Mining valid from 2022-05-12

Version of Record valid from 2022-05-12
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Article History

Received: 24 January 2022

Accepted: 16 April 2022

First Online: 12 May 2022

Declarations

:

: Ethical committee approval was granted by the institutional research ethics committee of participating hospitals. All procedures involving human participants were performed following the Helsinki declaration and its later amendments.

: The informed consent was waived for the retrospective analysis. All authors reviewed and approved the final version of the manuscript.

: The authors declare no conflicts of interest.

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