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Machine learning-based model development for predicting risk factors of prolonged intra-aortic balloon pump therapy in patients with coronary artery bypass grafting

Crossref DOI link: https://doi.org/10.1186/s13019-024-02830-8

Published Online: 2024-06-26

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

Authors

Yang, Changqing

Zheng, Peng

Li, Luo

Zhang, Qian

Luo, Zhouyu

Shi, Zhan

Zhao, Sheng

Li, Quanye
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Text and Data Mining valid from 2024-06-26

Version of Record valid from 2024-06-26
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Article History

Received: 18 February 2024

Accepted: 14 June 2024

First Online: 26 June 2024

Declarations

:

: The protocol of this study complied with the Declaration of Helsinki (revised in 2013) and was approved and supervised by the Ethics Committee of The First Affiliated Hospital of Nanjing Medical University (Approval number: 2019-SR-313.A1). Due to retrospective nature of this study, without any clinical interventions, patients’ informed consent was waived by the Ethics Review Committee of the hospital.

: Not applicable.

: The authors declare no competing interests.

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