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Application of machine learning missing data imputation techniques in clinical decision making: taking the discharge assessment of patients with spontaneous supratentorial intracerebral hemorrhage as an example

Crossref DOI link: https://doi.org/10.1186/s12911-022-01752-6

Published Online: 2022-01-13

Published Print: 2022-12

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

Authors

Wang, Huimin

Tang, Jianxiang

Wu, Mengyao

Wang, Xiaoyu

Zhang, Tao
Funding

Funding for this research was provided by:

Sichuan Province Science and Technology Support Program (2020YFS0015, 2020YFS0091, 2021YFS0001-LH, 2019-YF05-00333-SN, 2020YFS0015, 2020YFS0091, 2021YFS0001-LH, 2019-YF05-00333-SN)

Sichuan University (2018hhf-26, 2018HXFH010, 2018hhf-26, 2018HXFH010)

Health Commission of Sichuan province (20PJ092)

National Natural Science Foundation of China (81602935)

Chongqing Science and Technology Program (cstc2020jscx-cylhX0003)

Central government funding items (2021zc02)

Liangshan Yi autonomous prefecture Center for Disease Control and Prevention (H210322)
License Information

Text and Data Mining valid from 2022-01-13

Version of Record valid from 2022-01-13
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Article History

Received: 15 September 2021

Accepted: 6 January 2022

First Online: 13 January 2022

Declarations

:

: This study design was reviewed and approved by the Ethics Committee of Sichuan University (KS2020269). This study used de-identified data, and the waiver of informed consent was reviewed and approved by the Sichuan University Institutional Review Board.

: Not applicable.

: The authors declare that they have no competing interests.

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