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Cross-institutional evaluation of deep learning and radiomics models in predicting microvascular invasion in hepatocellular carcinoma: validity, robustness, and ultrasound modality efficacy comparison

Crossref DOI link: https://doi.org/10.1186/s40644-024-00790-9

Published Online: 2024-10-22

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

Authors

Zhang, Weibin

Guo, Qihui

Zhu, Yuli

Wang, Meng

Zhang, Tong

Cheng, Guangwen

Zhang, Qi

Ding, Hong
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (62071285)

Shanghai Science and Technology Development Foundation (22Y11911500)
License Information

Text and Data Mining valid from 2024-10-22

Version of Record valid from 2024-10-22
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Article History

Received: 7 September 2024

Accepted: 16 October 2024

First Online: 22 October 2024

Declarations

:

: This study was approved by the Huashan Hospital Institutional Review Board Fudan University (2022 − 841), and the Ethics Committee of Zhongshan Hospital Fudan University (B2022-223R), and informed consent was waived.

: Not applicable.

: The authors declare no competing interests.

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