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

PURPOSE: The study aimed to create a machine learning model (MLM) to predict the stone-free status (SFS) of patients undergoing percutaneous nephrolithotomy (PCNL) and compare its performance to the S.T.O.N.E. and Guy’s stone scores. PATIENTS AND METHODS: This is a retrospective study that included...

Descripción completa

Detalles Bibliográficos
Autores principales: AlAzab, Rami, Ghammaz, Owais, Ardah, Nabil, Al-Bzour, Ayah, Zeidat, Layan, Mawali, Zahraa, Ahmed, Yaman B, Alguzo, Tha’er Abdulkareem, Al-Alwani, Azhar Mohanad, Samara, Mahmoud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503523/
https://www.ncbi.nlm.nih.gov/pubmed/37720492
http://dx.doi.org/10.2147/IJNRD.S427404

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503523/
https://www.ncbi.nlm.nih.gov/pubmed/37720492
http://dx.doi.org/10.2147/IJNRD.S427404

Ejemplares similares