Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review-Reference-Cited by-同舟云学术

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Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review

Published:2024-08-01 Issue:8 Volume:38 Page:725-740
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Panthier Frédéric¹²³⁴^ORCID,Melchionna Alberto¹,Crawford-Smith Hugh¹,Phillipou Yiannis¹,Choong Simon¹,Arumuham Vimoshan¹,Allen Sian¹,Allen Clare⁵,Smith Daron¹⁶⁷

Affiliation:

1. Department of Urology, Westmoreland Street Hospital, UCLH NHS Foundation Trust, London, United Kingdom.

2. Sorbonne University GRC Urolithiasis No. 20 Tenon Hospital, Paris, France.

3. Progressive Endourological Association for Research and Leading Solutions (PEARLS), Paris, France.

4. PIMM, UMR 8006 CNRS-Arts et Métiers ParisTech, Paris, France.

5. Department of Radiology, University College London Hospitals, London, United Kingdom.

6. Endourology Academy.

7. Social Media Committee, Endourological Society.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2023.0717

Reference40 articles.

1. Epidemiology of Kidney Stones

3. Enabling national improvement in quality of care for renal colic

4. I.—COMPUTING MACHINERY AND INTELLIGENCE

5. 6. Chollet F. Deep Learning with Python. Manning Publications Co: Shelter Island, NY; 2018.

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