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

Asian Journal of Urology 2023年第3期10卷 258-274页

作者： Anastasios Anastasiadis Antonios Koudonas Georgios Langas Stavros Tsiakaras dimitrios memmos Ioannis Mykoniatis Evangelos NSymeonidis dimitrios Tsiptsios Eliophotos Savvides Ioannis Vakalopoulos Georgios Dimitriadis Jean de la Rosette 1st Department of Urology Aristotle University of ThessalonikiSchool of Medicine“G.Gennimatas”General HospitalThessalonikiGreece Neurology Department Democritus University of ThraceAlexandroupolisGreece Department of Urology Main Kinzig KlinikenGelnhausenGermany Department of Urology Istanbul Medipol Mega University HospitalIstanbulTurkey

Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone ***:A comprehensive literature review was performed using PubMed,Scopus,and Google Scholar databases to identify publications about innovative concepts or supporting applications of AI in the improvement of every medical procedure relating to stone *** terms“endourology”,“artificial intelligence”,“machine learning”,and“urolithiasis”were used for searching eligible reports,while review articles,articles referring to automated procedures without AI application,and editorial comments were excluded from the final set of *** search was conducted from January 2000 to September 2023 and included manuscripts in the English ***: A total of 69 studies were *** main subjects were related to the detection of urinary stones,the prediction of the outcome of conservative or operative management,the optimization of operative procedures,and the elucidation of the relation of urinary stone chemistry with various ***: AI represents a useful tool that provides urologists with numerous amenities,which explains the fact that it has gained ground in the pursuit of stone disease management *** effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing ***,little is known concerning the potential of this vast *** patient records,containing big data,offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment ***,the existing applications are not generalizable in real-life practice,and high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.

关键词： Artificial intelligence Urolithiasis Endourology Machine learning Stone disease

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