A machine learning algorithm grouped patients with chronic kidney disease into three distinct subgroups. Each subgroup was associated with different risks for disease progression, cardiovascular ...

SVM and kNN exemplify several important trade-offs in machine learning (ML). SVM is often less computationally demanding than kNN and is easier to interpret, but it can identify only a limited set ...

An approach that uses artificial intelligence by including cardiac biomarkers into a machine learning algorithm more accurately predicted atrial fibrillation in patients with chronic kidney ...

A retrospective study found that 3 machine learning models demonstrated equivalent predictability and greater sensitivity in the prognosis of chronic kidney disease (CKD) compared with the Kidney ...