Predicting the Postoperative Outcome of Percutaneous Nephrolithotomy with Machine Learning System: Software Validation and Comparative Analysis with Guy's Stone Score and the CROES Nomogram-Reference-Cited by-同舟云学术

Predicting the Postoperative Outcome of Percutaneous Nephrolithotomy with Machine Learning System: Software Validation and Comparative Analysis with Guy's Stone Score and the CROES Nomogram

Published:2020-06-01 Issue:6 Volume:34 Page:692-699
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Aminsharifi Alireza¹²,Irani Dariush¹,Tayebi Sona¹,Jafari Kafash Taher¹,Shabanian Tayebeh³,Parsaei Hossein³⁴

Affiliation:

1. Department of Urology, Shiraz University of Medical Sciences, Shiraz, Iran.

2. Laparoscopy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.

3. Department of Medical Physics and Engineering, Shiraz University of Medical Sciences, Shiraz, Iran.

4. Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.

Publisher

Mary Ann Liebert Inc

Subject

Urology

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2019.0475

Reference32 articles.

1. EAU Guidelines on Interventional Treatment for Urolithiasis

2. Surgical management of urolithiasis – a systematic analysis of available guidelines

3. The Guy's Stone Score—Grading the Complexity of Percutaneous Nephrolithotomy Procedures

4. A Nephrolithometric Nomogram to Predict Treatment Success of Percutaneous Nephrolithotomy

5. Seoul National University Renal Stone Complexity Score for Predicting Stone-Free Rate after Percutaneous Nephrolithotomy

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