Artificial Intelligence for Kidney Stone Spectra Analysis: Using Artificial Intelligence Algorithms for Quality Assurance in the Clinical Laboratory-Reference-Cited by-同舟云学术

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Artificial Intelligence for Kidney Stone Spectra Analysis: Using Artificial Intelligence Algorithms for Quality Assurance in the Clinical Laboratory

Published:2023-03 Issue:1 Volume:1 Page:1-12
ISSN:2949-7612
Container-title:Mayo Clinic Proceedings: Digital Health
language:en
Short-container-title:Mayo Clinic Proceedings: Digital Health

Author:

Day Patrick L.,Erdahl Sarah,Rokke Denise L.,Wieczorek Mikolaj,Johnson Patrick W.,Jannetto Paul J.,Bornhorst Joshua A.,Carter Rickey E.^ORCID

Publisher

Elsevier BV

Reference22 articles.

1. Kidney stone disease: an update on current concepts;Alelign;Adv Urol,2018

2. Kidney stones: a global picture of prevalence, incidence, and associated risk factors;Romero;Rev Urol,2010

3. Economic impact of urinary stones;Hyams;Transl Androl Urol,2014

4. Economics of stone disease/treatment;Strohmaier;Arab J Urol,2012

5. The ROKS nomogram for predicting a second symptomatic stone episode;Rule;J Am Soc Nephrol,2014

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial Intelligence in Urology: Application of a Machine Learning Model to Predict the Risk of Urolithiasis in a General Population;Journal of Endourology;2024-08-01

2. Evaluation and Classification of Kidney Stone Detection Using Deep Learning Techniques;2023 6th International Conference on Software Engineering and Computer Science (CSECS);2023-12-22

3. Assessment of Sigma Error Metrics Associated with Manual Secondary Result Review and Subsequent Artificial Intelligence-Driven Quality Assurance Review—Application to Kidney Stone Analysis;Clinical Chemistry;2023-11-25

4. Optimizing Kidney Stone Prediction through Urinary Analysis with Improved Binary Particle Swarm Optimization and eXtreme Gradient Boosting;Mathematics;2023-04-03

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