Objective Machine learning methods may have better or comparable predictive ability than
traditional analysis. We explore machine learning methods to predict the likelihood of acute …

Machine learning approach to predict acute kidney injury after liver surgery - PMC Back to
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The precise prediction of acute kidney injury (AKI) after nephrectomy for renal cell carcinoma
(RCC) is an important issue because of its relationship with subsequent kidney dysfunction …

Acute kidney injury (AKI) after liver transplantation has been reported to be associated with
increased mortality. Recently, machine learning approaches were reported to have better …

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

Objective To investigate the effect of 5 machine learning algorithms in predicting total
hepatocellular carcinoma (HCC) postoperative death outcomes. Methods This study was a …

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 …

Objective Acute kidney injury after cardiac surgery increases morbidity and mortality.
Diagnosis relies on oliguria or increased serum creatinine, which develop 48 to 72 hours …

Acute Kidney Injury (AKI) is a common complication after surgery. Recognition of patients at
risk of AKI at an earlier stage is a priority for researchers and health care providers. The …

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 …