Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy

Abstract

We applied a selected machine learning analysis to predict the result after treatment of SWL for urinary stone. About 88% accurate machine learning based predictive model was evaluated. The importance of machine learning algorithm can give matched insights to domain knowledge on effective and influential factors for SWL success outcomes.