Predicting the Stone-Free Status of Percutaneous Nephrolithotomy with the Machine Learning System.

Rami AlAzabOwais GhammazNabil ArdahAyah Nedal Al-BzourLayan ZeidatZahraa MawaliYaman B AhmedTha'er Abdulkareem AlguzoAzhar Mohanad Al-AlwaniMahmoud Samara

Published in: International journal of nephrology and renovascular disease (2023)

MLMs can be used with high accuracy in predicting SFS for patients undergoing PCNL. MLMs we utilized predicted the SFS with AUCs superior to those of GSS and S.T.O.N.E scores.

Keyphrases

machine learning
patients undergoing
minimally invasive
artificial intelligence
ultrasound guided
big data
radiofrequency ablation