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Development and validation of machine learning models to predict 30-day mortality in patients with cardiac arrest complicated by acute kidney injury

Crossref DOI link: https://doi.org/10.1016/j.clinsp.2026.101129

Published Print: 2026-01

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Yuan, Meng https://orcid.org/0000-0001-9982-3098
Zhong, Lei https://orcid.org/0000-0002-0208-1823
Min, Jie https://orcid.org/0000-0002-7629-5541
Ni, Mingxia https://orcid.org/0009-0005-9522-8554
Yao, Yufeng https://orcid.org/0009-0009-3591-8149
Funding

Funding for this research was provided by:

Zhejiang Provincial Health Commission

Medical and Health Research Project of Zhejiang Province (2025KY1546)
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Text and Data Mining valid from 2026-01-01

Text and Data Mining valid from 2026-01-01

Version of Record valid from 2026-08-28
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This article is maintained by: Elsevier

Article Title: Development and validation of machine learning models to predict 30-day mortality in patients with cardiac arrest complicated by acute kidney injury

Journal Title: Clinics

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.clinsp.2026.101129

Content Type: article

Copyright: © 2026 HCFMUSP. Published by Elsevier España, S.L.U.