Predicting Positive Repeat Prostate Biopsy Outcomes: Comparison of Machine Learning Approaches to Identify Key Parameters and Optimal Algorithms

CONCLUSIONS: We developed an SVC-based machine learning algorithm for predicting positive repeat prostate biopsy results. Our analysis revealed that initial and latest prostate volumes, initial and latest PSA levels, latest fPSA/PSA ratio and age are significant factors for this model.PMID:37867334 | DOI:10.56434/j.arch.esp.urol.20237607.61

Source: Archivos Espanoles de Urologia - October 23, 2023 Category: Urology & Nephrology Authors: Xinru Zhang Chao Feng Xiao Bai Xufeng Peng Qian Guo Lei Chen Jingdong Xue Source Type: research