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An interpretable machine learning model based on habitat radiomics combined with deep learning for predicting the WHO/ISUP grade of patients with clear cell renal cell carcinoma

Crossref DOI link: https://doi.org/10.1186/s12880-026-02285-4

Published Online: 2026-03-21

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

Authors

Tao, Xiang

Shan, Shuai

Chen, Xiaohui

Yu, Zejun

Qi, Hongliang
License Information

Text and Data Mining valid from 2026-03-21

Version of Record valid from 2026-04-30
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Article History

Received: 14 January 2026

Accepted: 10 March 2026

First Online: 21 March 2026

Declarations

:

: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.The study was conducted in accordance with the Declaration of Helsinki (as amended in 2013). The study was approved by the Medical Ethics Committee of Suzhou Yongding Hospital(202452). Due to the nature of the retrospective analysis, it is not necessary to obtain the written informed consent of the participants.

: Not applicable.

: The authors declare no competing interests.

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