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CT habitat radiomics and topological data analysis based on interpretable machine learning for prediction of pancreatic ductal adenocarcinoma pathological grading

Crossref DOI link: https://doi.org/10.1186/s12880-025-02094-1

Published Online: 2025-12-06

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

Authors

Song, Jiadong

Zhao, Tianyu

Zhang, Meng

Yang, Jinzhi

Zhu, Aonan

Qi, Xin

Yang, Chao

Dong, Yang
License Information

Text and Data Mining valid from 2025-12-06

Version of Record valid from 2026-01-12
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Article History

Received: 1 September 2025

Accepted: 26 November 2025

First Online: 6 December 2025

Declarations

:

: The study was approved by the Institutional Ethics Committee of the Second Hospital of Dalian Medical University (approval number: KY2024-023-01, approval date: 2024-05) and was conducted following the principles outlined in the Declaration of Helsinki. All authors read and approved the final manuscript. Due to its retrospective nature, the requirement for informed consent of patients is waived. All patients’ information was anonymous before analysis.

: Not applicable.

: The authors declare no competing interests.

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