engleski

Determination of the calcium oxalate urolithiasis risk in children using paralel algorithms constructed with C4.5 classifier.

We developed a machine learning computer program for the Calcium Oxalate urolithiasis risk in children. The method of analysis is based on C4.5 classifier machine learning algorithms. It is shown that the risk of Calcium Oxalate urolithiasis may be determined with 100% sensitivity and specificity, from few relevant biochemical parameters. Our results indicate that machine learning algorithms may be a potent prognostic tools in biomedicine.

urolithiasis; prognosis; C4.5 classifier; calcium oxalate; machine learning

nije evidentirano