Daniele Amparore, Sabrina De Cillis, Eugenio Alladio, Michele Sica, Federico Piramide, Paolo Verri, Enrico Checcucci, Alberto Piana, Alberto Quarà, Edoardo Cisero, Matteo Manfredi, Michele Di Dio, Cristian Fiori, Francesco Porpiglia
Introduction: Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabilitation after robot-assisted radical prostatectomy. Although nomograms exist, their retrospective limitations highlight artificial intelligence (AI)'s potential. This study seeks to develop a machine learning algorithm using robot-assisted radical prostatectomy (RARP) data to predict postoperative incontinence, advancing personalized care. Materials and Methods: In this propsective observational study, patients with localized prostate cancer undergoing RARP between April 2022 and January 2023 were assessed...
March 21, 2024: Journal of Endourology