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Machine learning prediction of postoperative acute kidney injury in aortic dissection patients using dynamic inflammatory markers and clinical features

Crossref DOI link: https://doi.org/10.1186/s12911-026-03443-y

Published Online: 2026-03-25

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

Authors

Xu, Yansong

Huang, Chunyan

Wang, Yuewu

Huang, Chanyu

Xie, Yuan

Liang, Guanbiao

Li, Caiying

Wei, Ruiying

Liu, Junting
Funding

Funding for this research was provided by:

Guangxi Clinical Key Specialty - Emergency Nursing Fund (QTKT20253792)
License Information

Text and Data Mining valid from 2026-03-25

Version of Record valid from 2026-05-04
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Article History

Received: 19 November 2025

Accepted: 16 March 2026

First Online: 25 March 2026

Declarations

:

: This study was approved by the ethics committee of The First Affiliated Hospital of Guangxi Medical University. All methods were carried out in accordance with Declaration of Helsinki. Written Informed consent was obtained from all participants/patients.

: Not applicable as no individual person’s data are contained in this manuscript in any identifiable form.

: Not application.

: The authors declare no competing interests.

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