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Development and validation of a risk prediction model for postoperative urinary retention after gynecologic abdominal-pelvic surgery

Abstract This study developed prediction models using 12 machine learning (ML) algorithms and, through comprehensive evaluation, selected the optimal model to predict postoperative urinary retention after gynecologic abdominal-pelvic surgery. An online calculator was created to provide reference for...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Jiahao Shi, Youbei Lin, Xiaojing Qin, Yinghui Gong, Hongyu Li
Format: Artigo
Sprache:Inglês
Veröffentlicht: Nature Portfolio 2025-12-01
Schriftenreihe:Scientific Reports
Schlagworte:
Urinary retention
Gynecologic surgery
Predictive modeling
Machine learning
Risk factors
Online-Zugang:https://doi.org/10.1038/s41598-025-32714-3
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