Machine learning models for screening clinically significant nephrolithiasis in overweight and obese populations-Reference-Cited by-同舟云学术

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Machine learning models for screening clinically significant nephrolithiasis in overweight and obese populations

Published:2024-03-09 Issue:1 Volume:42 Page:
ISSN:1433-8726
Container-title:World Journal of Urology
language:en
Short-container-title:World J Urol

Author:

Chen Hao-Wei,Lee Jung-Ting,Wei Pei-Siou,Chen Yu-Chen,Wu Jeng-Yih,Lin Chia-I.,Chou Yii-Her,Juan Yung-Shun,Wu Wen-Jeng,Kao Chung-Yao^ORCID

Funder

National Science and Technology Council

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00345-024-04826-4.pdf

Reference27 articles.

1. Romero V, Akpinar H, Assimos DG (2010) Kidney stones: a global picture of prevalence, incidence, and associated risk factors. Rev Urol 12(2–3):e86

2. Ziemba JB, Matlaga BR (2017) Epidemiology and economics of nephrolithiasis. Investig Clin Urol 58(5):299–306

3. Pearle MS et al (2005) Urologic diseases in America project: urolithiasis. J Urol 173(3):848–857

4. Robson J et al (2016) The NHS health check in England: an evaluation of the first 4 years. BMJ Open 6(1):e008840

5. Smith-Bindman R et al (2014) Ultrasonography versus computed tomography for suspected nephrolithiasis. N Engl J Med 371(12):1100–1110

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