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Annals of Clinical and Analytical Medicine

ACAM
E-ISSN: 2667-663X · Monthly · English

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Intraoperative pelvic urine volume as a machine learning predictor of recurrence after pediatric pyeloplasty

ML prediction of recurrent UPJ obstruction

Original Research doi:10.4328/ACAM.22901 Published: 01.06.2026 Ann Clin Anal Med 2026;17(6):566-571

Authors

1, 1, 1, 2, 3, 1, 1
Affiliations

1Department of Urology, Faculty of Medicine, Çukurova University, Adana, Türkiye.

2Department of Artificial Intelligence Engineering, Faculty of Computer and Informatics, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye.

3Urology Clinic, Defne State Hospital, Hatay, Türkiye.

Corresponding Author

Tunahan Ates

drtunahanates0101@gmail.com

+90 531 344 75 62

Declarations

Ethics Declarations

The authors declare that all procedures performed in this study were conducted in accordance with institutional, national, and international ethical standards.

Animal and Human Rights Statement

All procedures involving human participants were conducted in accordance with the Declaration of Helsinki and its later amendments.

Informed Consent

Due to the retrospective nature of the study and the use of anonymized data, informed consent was waived by the Ethics Committee.

Data Availability

The datasets used and/or analyzed during the current study are not publicly available due to patient privacy reasons but are available from the corresponding author on reasonable request.

Conflict of Interest

The authors declare that there is no conflict of interest.

Funding

None.

Author Contributions (CRediT Taxonomy)

Conceptualization: İ.O.Y., N.A.

Methodology: İ.O.Y., O.Y.

Software: O.Y.

Validation: M.G.A., N.S.

Formal Analysis: O.Y., İ.O.Y.

Investigation: T.A., M.D.

Data Curation: T.A., M.D.

Writing – Original Draft: İ.O.Y., O.Y.

Writing – Review & Editing: N.A., M.G.A., N.S.

Supervision: N.S.

References

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Figures

Figure 1. Receiver operating characteristic (ROC) curves comparison of the alghoritms

Figure 1. Receiver operating characteristic (ROC) curves comparison of the alghoritms

Figure 2. Best random forest model receiver operating characteristics curve

Figure 2. Best random forest model receiver operating characteristics curve

Figure 3. Decision tree training

Figure 3. Decision tree training

Figure 4. Feature importance analysis

Figure 4. Feature importance analysis

Tables

Table 1. Features list and outcomes

Table 1. Features list and outcomes

Abbreviations: HN = hydronephrosis; A-P = antero-posterior; PCN = percutaneous nephros- tomy; D-J = double-j.

Table 2. Comparison of complications between the Cured and Recurrence groups as stratified by the modified Clavien system

Table 2. Comparison of complications between the Cured and Recurrence groups as stratified by the modified Clavien system

Abbreviations: D-J = Double J.

About This Article

How to Cite This Article

İsmail Onder Yilmaz, Nebil Akdogan, Mehmet Gurkan Arikan, Ozgur Yilmaz, Tunahan Ates, Mutlu Deger, Nihat Satar. Intraoperative pelvic urine volume as a machine learning predictor of recurrence after pediatric pyeloplasty. Ann Clin Anal Med 2026;17(6):566-571. doi:10.4328/ACAM.22901

Publication History

Received:
16.09.2025
Accepted:
03.11.2025
Published Online:
06.12.2025
Printed:
01.06.2026