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Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach

Crossref DOI link: https://doi.org/10.1186/s12872-025-04759-9

Published Online: 2025-05-10

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

Authors

Li, Zhenzhen

Fan, Jianing

Fan, Jiajun

Miao, Jiaxin

Lin, Dawei

Zhao, Jingyan

Zhang, Xiaochun

Pan, Wenzhi

Zhou, Daxin

Ge, Junbo
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (T2288101, T2288101, T2288101)
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Text and Data Mining valid from 2025-05-10

Version of Record valid from 2025-05-10
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Article History

Received: 25 November 2024

Accepted: 11 April 2025

First Online: 10 May 2025

Declarations

:

: This study was approved by the Ethics Committee of Zhongshan Hospital, Fudan University (Approval No.: B2020-039),and all patients provided signed an informed consent form.

: Not applicable.

: Informed consent was obtained from all subjects involved in the study.

: The authors declare no competing interests.

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