David Shveiky

Individualized Prediction of Recurrence Following Uterine-Preserving Pelvic Organ Prolapse Repair Using Internally Validated Machine Learning Models

Background/Objectives: Approximately 11–20% of women affected by pelvic organ prolapse (POP) will undergo surgical intervention during their lifetime and nearly one-third of these women will require an additional procedure due to recurrence or failure of the initial repair. This...