基于人工智能的方法对尿石症治疗的变革：一项全面综述
Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review.
作者信息
Anastasiadis Anastasios, Koudonas Antonios, Langas Georgios, Tsiakaras Stavros, Memmos Dimitrios, Mykoniatis Ioannis, Symeonidis Evangelos N, Tsiptsios Dimitrios, Savvides Eliophotos, Vakalopoulos Ioannis, Dimitriadis Georgios, de la Rosette Jean
机构信息
1st Department of Urology, Aristotle University of Thessaloniki, School of Medicine, "G.Gennimatas" General Hospital, Thessaloniki, Greece.
Neurology Department, Democritus University of Thrace, Alexandroupolis, Greece.
出版信息
Asian J Urol. 2023 Jul;10(3):258-274. doi: 10.1016/j.ajur.2023.02.002. Epub 2023 May 2.
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.
目的
对目前关于人工智能（AI）在尿路结石疾病评估与管理中的应用研究及证据进行全面综述。
方法
使用PubMed、Scopus和谷歌学术数据库进行全面的文献综述，以确定关于AI在改善与结石疾病相关的各项医疗程序中的创新概念或支持性应用的出版物。搜索词使用“腔内泌尿外科”“人工智能”“机器学习”和“尿石症”来查找符合条件的报告，而综述文章、提及无AI应用的自动化程序的文章以及编辑评论被排除在最终出版物集之外。搜索时间为2000年1月至2023年9月，纳入英文稿件。
结果
共识别出69项研究。主要主题涉及尿路结石的检测、保守或手术治疗结果的预测、手术程序的优化以及尿石化学与各种因素关系的阐明。
结论
AI是一种有用的工具，为泌尿外科医生提供了众多便利，这解释了它在追求结石疾病管理完善方面获得进展的事实。将其作为现有数据的替代或辅助手段可提高诊断和治疗的有效性。然而，对于这个广阔领域的潜力知之甚少。包含大数据的电子病历为AI提供了开发和分析更精确高效的诊断与治疗算法的机会。尽管如此，现有应用在实际临床实践中无法普遍适用，需要高质量研究来确立AI在尿路结石疾病管理中的整合应用。
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