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Prediction of surgical necessity in children with ureteropelvic junction obstruction using machine learning.

Ir J Med Sci

January 2025

Faculty of Medicine, Department of Pediatric Surgery Division of Pediatric Urology, Eskisehir Osmangazi University, Eskişehir, Turkey.

Background: Hydronephrosis developing at the ureteropelvic junction due to obstruction poses clinical challenges as it has the potential to cause renal damage.

Aims: This study aims to evaluate how well machine learning models such, as XGBClassifier and Logistic Regression can be used to predict the need for treatment in patients, with hydronephrosis resulting from ureteropelvic junction obstruction.

Methods: Hydronephrosis was diagnosed in the medical records of patients from January 2015 to December 2020.

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