Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review-Reference-Cited by-同舟云学术

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Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review

Published:2024-07-31 Issue:2 Volume:46 Page:
ISSN:0886-022X
Container-title:Renal Failure
language:en
Short-container-title:Renal Failure

Author:

Li Jie¹²,Zhu Manli¹²,Yan Li¹²

Affiliation:

1. Department of Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

2. Department of Emergency, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0886022X.2024.2380748

Reference79 articles.

1. Global epidemiology and outcomes of acute kidney injury

2. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study

3. World Incidence of AKI: A Meta-Analysis

4. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study

5. Acute Kidney Injury in Critically Ill Patients with Sepsis: Clinical Characteristics and Outcomes

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