Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction-Reference-Cited by-同舟云学术

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Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction

Published:2024-09-12 Issue: Volume: Page:
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Song Jonathan J¹,Kielhofner Jane²,Qian Zhiyu (Jason)²,Gu Catherine²,Boysen William²,Chang Steven³,Dahl Douglas⁴,Eswara Jairam²,Haleblian George E.⁵,Wintner Anton⁶,Wollin Daniel A²

Affiliation:

1. Boston University Chobanian & Avedisian School of Medicine, 72 E Concord St, Boston, Boston, Massachusetts, United States, 02118;

2. Brigham and Women's Hospital, Department of Urology, Boston, Massachusetts, United States;

3. Brigham and Women's Hospital, Division of Urology and Center for Surgery and Public Health, Boston, Massachusetts, United States;

4. Massachusetts General Hospital, Urology, Boston, Massachusetts, United States;

5. Brigham and Women's Hospital, Urology, 45 Francis St, Boston, Massachusetts, United States, 02115, ;

6. Massachusetts General Hospital, Department of Urology, Boston, Massachusetts, United States;

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2024.0264

Reference21 articles.

1. Predictors of Recoverability of Renal Function after Pyeloplasty in Adults with Ureteropelvic Junction Obstruction

2. Laparoscopic management of recurrent ureteropelvic junction obstruction following pyeloplasty: a single surgical team experience with 38 cases

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