Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning
Background Predicting the successful weaning of acute kidney injury (AKI) patients from renal replacement therapy (RRT) has emerged as a research focus, and we successfully built predictive models for RRT withdrawal in patients with severe AKI by machine learning.Methods This retrospective single-ce...
Saved in:
| Main Authors: | Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Renal Failure |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2319329 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of Modified Ventilator Bundle and Its Effect on Weaning and Ventilation Days among Critical Ill Patients
by: Amany S. Eweas, et al.
Published: (2024-02-01) -
Predictors for short-term successful weaning from continuous renal replacement therapy: a systematic review and meta-analysis
by: Yu Li, et al.
Published: (2023-12-01) -
SACrA score to predict the initiation of renal replacement therapy in critically ill patients: a single-center retrospective study
by: Ginga Suzuki, et al.
Published: (2024-12-01) -
Evaluation of abdominal expiratory muscle thickness pattern, diaphragmatic excursion, diaphragmatic thickness fraction and lung ultrasound score in critically ill patients and their association with weaning patterns: A prospective study
by: Priyanka Bansal, et al.
Published: (2025-04-01) -
Value of combining lung ultrasound score with oxygenation and functional indices in determining weaning timing for critically ill pediatric patients
by: Ximeng Hao, et al.
Published: (2025-01-01)