Predicting congenital anomalies of the kidney and urinary tract (CAKUT) in prenatal hydronephrosis via machine learning.

Saved in:
Bibliographic Details
Title: Predicting congenital anomalies of the kidney and urinary tract (CAKUT) in prenatal hydronephrosis via machine learning.
Authors: Taner S; Pediatric Nephrology, Adana City Training and Research Hospital, Adana, Turkey. sevgintaner@gmail.com.; Pediatric Nephrology, Ege University Faculty of Medicine, İzmir, Turkey. sevgintaner@gmail.com., Özgür S; Ege University Translational Pulmonary Research Center-EgeSAM, İzmir, Turkey.; Regional Hub for Cancer Registration in Northern Africa, Central and Western Asia, IARC İzmir Hub, WHO/IACR GICR, İzmir, Turkey., Yıldırım GA; Pediatrics, Adana City Training and Research Hospital, Adana, Turkey., Ekberli G; Pediatric Urology, Adana City Training and Research Hospital, Adana, Turkey.
Source: World journal of urology [World J Urol] 2025 Dec 04; Vol. 44 (1), pp. 13. Date of Electronic Publication: 2025 Dec 04.
Publication Type: Journal Article
Journal Info: Publisher: Springer International Country of Publication: Germany NLM ID: 8307716 Publication Model: Electronic Cited Medium: Internet ISSN: 1433-8726 (Electronic) Linking ISSN: 07244983 NLM ISO Abbreviation: World J Urol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1433-8726
DOI:10.1007/s00345-025-06105-2