Artificial Intelligence in Urology: Application of a Machine Learning Model to Predict the Risk of Urolithiasis in a General Population-Reference-Cited by-同舟云学术

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Artificial Intelligence in Urology: Application of a Machine Learning Model to Predict the Risk of Urolithiasis in a General Population

Published:2024-08-01 Issue:8 Volume:38 Page:712-718
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Sánchez Catherine¹²^ORCID,Larenas Francisca²³^ORCID,Arroyave Juan Sebastián⁴^ORCID,Connors Christopher⁴,Giménez Belén²³,Palese Michael A.⁴,Fulla Juan¹²³^ORCID

Affiliation:

1. Clínica MEDS, Santiago, Chile.

2. Faculty of Medicine, University of Chile, Santiago, Chile.

3. Department of Urology, Hospital Clínico San Borja Arriarán, Santiago, Chile.

4. Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2023.0702

Reference23 articles.

1. The Ascent of Artificial Intelligence in Endourology: a Systematic Review Over the Last 2 Decades

2. Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review

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

4. Use of Artificial Intelligence for Analyzing Kidney Stone Composition: Are We There Yet?

5. Quality Assessment of Urinary Stone Analysis: Results of a Multicenter Study of Laboratories in Europe

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