Personalized application of machine learning algorithms to identify pediatric patients at risk for recurrent ureteropelvic junction obstruction after dismembered pyeloplasty-Reference-Cited by-同舟云学术

Personalized application of machine learning algorithms to identify pediatric patients at risk for recurrent ureteropelvic junction obstruction after dismembered pyeloplasty

Published:2021-11-13 Issue: Volume: Page:
ISSN:0724-4983
Container-title:World Journal of Urology
language:en
Short-container-title:World J Urol

Author:

Drysdale Erik,Khondker Adree^ORCID,Kim Jin K.,Kwong Jethro C. C.,Erdman Lauren,Chua Michael,Keefe Daniel T.,Lolas Marisol,Dos Santos Joana,Tasian Gregory,Rickard Mandy,Lorenzo Armando J.^ORCID

Funder

american urological association foundation

Publisher

Springer Science and Business Media LLC

Subject

Urology

Link

https://link.springer.com/content/pdf/10.1007/s00345-021-03879-z.pdf

Reference31 articles.

1. Salem YH, Majd M, Rushton HG et al (1995) Outcome analysis of pediatric pyeloplasty as a function of patient age, presentation and differential renal function. J Urol 154:1889–1893

2. Seixas-Mikelus SA, Jenkins LC, Williot P et al (2009) Pediatric pyeloplasty: comparison of literature meta-analysis of laparoscopic and open techniques with open surgery at a single institution. J Urol 182:2428–2434

3. Braga LHP, Lorenzo AJ, Skeldon S et al (2007) Failed pyeloplasty in children: comparative analysis of retrograde endopyelotomy versus redo pyeloplasty. J Urol 178:2571–2575