Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms-Reference-Cited by-同舟云学术

Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms

Published:2024-08-19 Issue:1 Volume:56 Page:
ISSN:0785-3890
Container-title:Annals of Medicine
language:en
Short-container-title:Annals of Medicine

Author:

Wang Yongbin¹²,Sun Xu²³^ORCID,Lu Jianhong¹²^ORCID,Zhong Lei¹²^ORCID,Yang Zhenzhen²⁴

Affiliation:

1. Department of Intensive Care Unit, Huzhou Central Hospital, Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, China

2. Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, China

3. Department of General Surgery, Huzhou Central Hospital, Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, China

4. Department of Nephrology, Huzhou Central Hospital, Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/07853890.2024.2388709

Reference28 articles.

1. Failure to Rescue After Severe Acute Kidney Injury in Patients Undergoing Non–Cardiac Surgery

2. Acute kidney injury and risk of cardiovascular outcomes: A nationwide cohort study

3. Timing of renal replacement therapy initiation for acute kidney injury in critically ill patients: a systematic review of randomized clinical trials with meta-analysis and trial sequential analysis

4. Inverse Correlation Between Incidence and Mortality of Acute Kidney Injury in Critically Ill Patients: A Systematic Review

5. Predictors for mortality and recovery in patients with acute renal injury receiving continuous renal replacement therapy