Multi-institutional Validation of Improved Vesicoureteral Reflux Assessment With Simple and Machine Learning Approaches-Reference-Cited by-同舟云学术

Multi-institutional Validation of Improved Vesicoureteral Reflux Assessment With Simple and Machine Learning Approaches

Published:2022-12 Issue:6 Volume:208 Page:1314-1322
ISSN:0022-5347
Container-title:Journal of Urology
language:en
Short-container-title:Journal of Urology

Author:

Khondker Adree¹^ORCID,Kwong Jethro C. C.²,Yadav Priyank¹,Chan Justin Y. H.²,Singh Anuradha³,Skreta Marta⁴⁵,Erdman Lauren⁴⁵,Keefe Daniel T.¹²⁶,Fischer Katherine⁷,Tasian Gregory⁷,Hannick Jessica H.⁸,Papanikolaou Frank¹⁹,Cooper Benjamin J.¹⁰,Cooper Christopher S.¹⁰,Rickard Mandy¹,Lorenzo Armando J.¹²

Affiliation:

1. Division of Urology, The Hospital for Sick Children, Toronto, Ontario, Canada

2. Division of Urology, Department of Surgery, University of Toronto, Toronto, Ontario, Canada

3. Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada

4. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

5. Vector Institute, Toronto, Ontario, Canada

6. Department of Surgery, IWK Hospital, Halifax, Nova Scotia, Canada

7. Division of Urology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania

8. Division of Pediatric Urology, UH Rainbow Babies and Children's Hospital, Cleveland, Ohio

9. Division of Urology, Trillium Health Partners, Mississauga, Ontario, Canada

10. Department of Urology, University of Iowa Hospitals and Clinics, Iowa City, Iowa

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Urology

Link

http://www.auajournals.org/doi/pdf/10.1097/JU.0000000000002987

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