Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review
Work
Year: 2024
Type: review
Source: Journal of Endourology
Authors F. Panthier, Alberto Melchionna, Hugh Crawford‐Smith, Yiannis Phillipou, Simon Choong +4 more
Institutions Centre National de la Recherche Scientifique, University College London Hospitals NHS Foundation Trust, University College London, Hôpital Tenon, Sorbonne Université +3 more
Cites: 39
Cited by: 5
Related to: 10
FWCI: 1.669
Citation percentile (by year/subfield): 99.95
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Sustainable Development Goal Zero hunger
Open Access status: closed