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

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 

机构地区：[1]1st Department of Urology,Aristotle University of Thessaloniki,School of Medicine,“G.Gennimatas”General Hospital,Thessaloniki,Greece [2]Neurology Department,Democritus University of Thrace,Alexandroupolis,Greece [3]Department of Urology,Main Kinzig Kliniken,Gelnhausen,Germany [4]Department of Urology,Istanbul Medipol Mega University Hospital,Istanbul,Turkey

出　　处：《Asian Journal of Urology》2023年第3期258-274,共17页亚洲泌尿外科杂志（英文）

摘　　要：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 disease.Methods: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 disease.The 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 publications.The search was conducted from January 2000 to September 2023 and included manuscripts in the English language.Results: A total of 69 studies were identified.The 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 factors.Conclusion: 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 perfection.The effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing data.However,little is known concerning the potential of this vast field.Electronic patient records,containing big data,offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms.Nevertheless,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 

分 类 号：R69[医药卫生—泌尿科学]