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Open Access

Peer-reviewed

Research Article

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium

Xiaoli Shen ,

Roles Conceptualization, Investigation, Methodology, Project administration, Resources, Software, Writing – original draft

* E-mail: rushuyan@126.com

Affiliation Department of Emergency Medicine, Huishan 3rd People’s Hospital of Wuxi City, Wuxi, China
⨯
Dongfeng Shang ,

Roles Methodology, Project administration, Resources, Validation, Visualization

* E-mail: rushuyan@126.com

Affiliation Department of Clinical Laboratory, Huishan 3rd People’s Hospital of Wuxi City, Wuxi, China
⨯
Weize Sun,

Roles Resources, Software, Supervision, Validation, Visualization

Affiliation Department of Emergency Medicine, Huishan 3rd People’s Hospital of Wuxi City, Wuxi, China
⨯
Shuyan Ru

Roles Funding acquisition

* E-mail: rushuyan@126.com

Affiliation Department of Critical Care, Huishan 3rd People’s Hospital of Wuxi City, Wuxi, China

https://orcid.org/0009-0007-3104-0362

⨯

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium

Xiaoli Shen,
Dongfeng Shang,
Weize Sun,
Shuyan Ru

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Published: April 9, 2025
https://doi.org/10.1371/journal.pone.0319519

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Sepsis
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Death rates
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Forecasting
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Intensive care units
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Machine learning
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Machine learning algorithms
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Medical risk factors
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