Background: Early identification of patients at high-risk of postoperative acute kidney injury
(AKI) can facilitate the development of preventive approaches. This study aimed to develop …

Objective Postoperative acute kidney injury (PO-AKI) is a common complication after cardiac
surgery. We aimed to evaluate whether machine learning algorithms could significantly …

Machine learning approaches were introduced for better or comparable predictive ability
than statistical analysis to predict postoperative outcomes. We sought to compare the …

Background Acute kidney injury (AKI) is a serious complication after cardiac surgery. We
derived and internally validated a Machine Learning preoperative model to predict cardiac …

Background: We aimed to develop and validate an automated machine learning (autoML)
prediction model for cardiac surgery-associated acute kidney injury (CSA-AKI). Methods …

Background Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common
complication following cardiac surgery. Early prediction of CSA-AKI is of great significance …

Cardiac surgery-associated acute kidney injury (CSA-AKI) is the most prevalent major
complication of cardiac surgery and exerts a negative effect on a patient's prognosis, thereby …

Purpose To establish novel prediction models for predicting acute kidney injury (AKI) after
cardiac surgery based on early postoperative biomarkers. Patients and methods This study …

This study developed and validated a machine learning model to accurately predict acute
kidney injury (AKI) after non-cardiac surgery, aiming to improve patient outcomes by …

Background To derive and validate a machine learning (ML) prediction model of acute
kidney injury (AKI) that could be used for AKI surveillance and management to improve …