Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury

Objectives This study aims to develop and validate a prediction model in-hospital mortality in critically ill patients with sepsis-associated acute kidney injury (SA-AKI) based on machine learning algorithms.Methods Patients who met the criteria for inclusion were identified in the Medical Informati...

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Autors principals:	Tianyun Gao, Zhiqiang Nong, Yuzhen Luo, Manqiu Mo, Zhaoyan Chen, Zhenhua Yang, Ling Pan
Format:	Artigo
Idioma:	Inglês
Publicat:	Taylor & Francis Group 2024-12-01
Col·lecció:	Renal Failure
Matèries:	Sepsis acute kidney injury prediction model of prognosis machine learning algorithms
Accés en línia:	https://www.tandfonline.com/doi/10.1080/0886022X.2024.2316267
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