Predicting Postoperative Stress Urinary Incontinence After Prolapse Surgery via Machine Learning and Regression Models: Development and Validation Study

This study developed 5 prediction models for postoperative SUI following prolapse surgery, which demonstrated good performance in internal validation. Among them, the SVM prediction model appeared to be the most promising. However, further external validation data are required to assess its generalizability. This model has the potential to become a high-quality clinical risk prediction tool for postoperative SUI in patients with prolapse, guiding clinical decisions on whether concurrent prolapse and incontinence surgeries are necessary.