Development and Validation of Risk Assessment Model for Pelvic Organ Prolapse Based on A Retrospective Study with Machine Learning Algorithms.
International Urogynecology Journal（2025）
Key words
Machine learning,Pelvic organ prolapse,Risk assessment model,Shapley additive explanations method
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