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Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice

Crossref DOI link: https://doi.org/10.1186/s12967-025-06402-9

Published Online: 2025-03-31

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

Authors

Zhou, Jie https://orcid.org/0000-0003-4472-9349
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Text and Data Mining valid from 2025-03-31

Version of Record valid from 2025-03-31
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Article History

Received: 28 December 2024

Accepted: 19 March 2025

First Online: 31 March 2025

Declarations

:

: All data were collected from the TCGA database () and TCIA database (). TCGA and TCIA belong to public databases. The patients involved in the database have obtained ethical approval. Users can download relevant data free for research and publication of relevant articles. Our study is based on open-source data, so there are no ethical issues and other conflict of interests.

: Not applicable.

: The authors declare no competing interests.

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