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Acute Kidney Injury

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Bibliometric and visual analysis of machine learning-based research in acute kidney injury worldwide.

Frontiers in public health
BACKGROUND: Acute kidney injury (AKI) is a serious clinical complication associated with adverse short-term and long-term outcomes. In recent years, with the rapid popularization of electronic health records and artificial intelligence machine learni...

Predicting outcomes of continuous renal replacement therapy using body composition monitoring: a deep-learning approach.

Scientific reports
Fluid balance is a critical prognostic factor for patients with severe acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT). This study evaluated whether repeated fluid balance monitoring could improve prognosis in this cli...

High-throughput image analysis with deep learning captures heterogeneity and spatial relationships after kidney injury.

Scientific reports
Recovery from acute kidney injury can vary widely in patients and in animal models. Immunofluorescence staining can provide spatial information about heterogeneous injury responses, but often only a fraction of stained tissue is analyzed. Deep learni...

Comparison between ketorolac- and fentanyl-based patient-controlled analgesia for acute kidney injury after robot-assisted radical prostatectomy: a retrospective propensity score-matched analysis.

World journal of urology
PURPOSE: It is unclear whether ketorolac-based patient-controlled analgesia (PCA) leads to acute kidney injury (AKI) after robot-assisted radical prostatectomy (RARP) in patients susceptible to AKI. We compared the postoperative AKI incidence with ke...

Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach.

Journal of biomedical informatics
OBJECTIVE: Acute kidney injury (AKI), a common condition on the intensive-care unit (ICU), is characterized by an abrupt decrease in kidney function within a few hours or days, leading to kidney failure or damage. Although AKI is associated with poor...

A deep learning-based dynamic model for predicting acute kidney injury risk severity in postoperative patients.

Surgery
BACKGROUND: Acute kidney injury is a common postoperative complication affecting between 10% and 30% of surgical patients. Acute kidney injury is associated with increased resource usage and chronic kidney disease development, with more severe acute ...

Prediction of Postoperative Creatinine Levels by Artificial Intelligence after Partial Nephrectomy.

Medicina (Kaunas, Lithuania)
: Multiple factors are associated with postoperative functional outcomes, such as acute kidney injury (AKI), following partial nephrectomy (PN). The pre-, peri-, and postoperative factors are heavily intertwined and change dynamically, making it diff...

Quantifying acute kidney injury in an Ischaemia-Reperfusion Injury mouse model using deep-learning-based semantic segmentation in histology.

Biology open
This study focuses on ischaemia-reperfusion injury (IRI) in kidneys, a cause of acute kidney injury (AKI) and end-stage kidney disease (ESKD). Traditional kidney damage assessment methods are semi-quantitative and subjective. This study aims to use a...

Can Simplified PADUA Renal (SPARE) Nephrometry scoring system help predict renal function outcomes after robot-assisted partial nephrectomy? (UroCCR study 93).

Minerva urology and nephrology
BACKGROUND: The SPARE Nephrometry Score (NS) is described as easier to implement than the RENAL and PADUA NSs, currently more widely used. Our objective was to compare the accuracy of SPARE NS in predicting renal function outcomes following RAPN.

An interpretable machine learning model to predict off-pump coronary artery bypass grafting-associated acute kidney injury.

Advances in clinical and experimental medicine : official organ Wroclaw Medical University
BACKGROUND: Off-pump coronary artery bypass grafting-associated acute kidney injury (OPCAB-AKI) is related to 30-day perioperative mortality. Existing mathematical models cannot be applied to help clinicians make early diagnosis and intervention deci...