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Diagnostic performance of deep learning and computational fluid dynamics-based instantaneous wave-free ratio derived from computed tomography angiography

Crossref DOI link: https://doi.org/10.1186/s12872-022-02469-0

Published Online: 2022-02-05

Published Print: 2022-12

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

Authors

Zhang, Jingyuan

Xu, Kun

Hu, Yumeng

Yang, Lin

Leng, Xiaochang

Jin, Hongfeng

Tang, Yiming

Liu, Xiaowei

Ye, Chen

Guo, Yitao

Wang, Lei

Zhang, Jianjun

Feng, Yue

Mou, Caiyun

Tang, Lijiang

Xiang, Jianping

Du, Changqing
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (81500284)

Major medical and health science and technology plan of Zhejiang Province (WKJ-ZJ-1913)

Natural Science Foundation of Zhejiang Province (L Y21H020002)
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Text and Data Mining valid from 2022-02-05

Version of Record valid from 2022-02-05
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Article History

Received: 22 October 2021

Accepted: 13 January 2022

First Online: 5 February 2022

Declarations

:

: This study was approved by the Zhejiang Hospital Ethics Review Committee and conducted according to the principles of the Declaration of Helsinki (as revised in 2013). Since this clinical study was a retrospective analysis of the information of previous cases, without direct contact with the subjects and subject privacy protection, the risk borne by the subjects was not greater than the minimum risk. The Zhejiang Hospital Ethics Review Committee agreed to exempt informed consent after review.

: Not applicable.

: The authors declare that they have no competing interests.

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