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A radiomics feature-based machine learning models to detect brainstem infarction (RMEBI) may enable early diagnosis in non-contrast enhanced CT

Published Online: 2022-09-28

Authors

Zhang, Haiyan

Chen, Hongyi

Zhang, Chao

Cao, Aihong

Lu, Qingqing

Wu, Hao

Zhang, Jun

Geng, Daoying
Funding

Funding for this research was provided by:

National Key R&D Program of China (2019YFC0120602)

Shanghai Municipal Commission of Science and Technology (No. 19411951200, No. 22S31905300)

Greater Bay Area Institute of Precision Medicine (No. KCH2310094)

Industrial Technology Research Institute Medical-Industrial Integration Project (No. IDH2310046)

Clinical Research Plan of SHDC (SHDC2020CR3020A)

Jiangsu Commission of Health (No. H2019090)
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Text and Data Mining valid from 2022-09-28

Version of Record valid from 2022-09-28
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Article History

Received: 30 May 2022

Revised: 21 July 2022

Accepted: 24 August 2022

First Online: 28 September 2022

Declarations

:

: The scientific guarantor of this publication is Daoying Geng.

: The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

: The authors Hongyi Chen and Chao Zhang did statistical analyses.

: Written informed consent was waived by the Institutional Review Board.

: Institutional Review Board approval was obtained.

: • Retrospective• Diagnostic or prognostic study• Performed at multi-institution

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