PURPOSE To analyze the bibliometric publication trend on the application of "Artificial Intelligence (AI) and its subsets (Machine Learning-ML, Virtual reality-VR, Radiomics) in Urolithiasis" over the last 3 decades. We looked at the publication trends associated with AI and stone disease, including both clinical and surgical applications, and training in endourology. METHODS Though a MeshTerms research on PubMed, we performed a comprehensive review from 1994-2023 for all published papers on "AI, ML, VR and Radiomics". Papers were then divided in three categories: A-Clinical (Non-surgical), B-Clinical (Surgical) and C-Training papers, and articles were then assigned to 3 periods: Period-1 (1994-2003), Period-2 (2004-2013), Period-3 (2014-2023). RESULTS 343 papers were noted (Groups A-129, B-163 and C-51), and trends increased from Period-1 to Period-2 at 123% (p=0.009), and to period-3 at 453% (p=0.003). This increase from Period-2 to Period-3 for groups A, B and C was 476% (p=0.019), 616% (0.001) and 185% (p<0.001) respectively. Group A papers included rise in papers on "stone characteristics" (+2100%;p=0.011), "renal function" (p=0.002), "stone diagnosis" (+192%), "prediction of stone passage" (+400%) and "quality of life" (+1000%). Group B papers included rise in papers on "URS" (+2650%,p=0.008), "PCNL" (+600%, p=0.001) and "SWL" (+650%,p=0.018). Papers on "Targeting" (+453%,p<0.001), "Outcomes" (+850%,p=0.013) and "Technological Innovation" (p=0.0311) had rising trends. Group C papers included rise in papers on "PCNL" (+300%,p=0.039), and "URS" (+188%,p=0.003). CONCLUSION Publications on AI and its subset areas for urolithiasis have seen an exponential increase over the last decade, with an increase in surgical and non-surgical clinical areas as well as in training. Future AI related growth in the field of endourology and urolithiasis is likely to improve training, patient centered decision making and clinical outcomes.

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文献 (PubMed) 中发表的过去 30 年（1994-2023 年）“尿石症中的人工智能、机器学习、虚拟现实和放射组学”的趋势：综合综述。

目的 分析过去 3 年来“人工智能 (AI) 及其子集（机器学习-ML、虚拟现实-VR、放射组学）在尿石症中应用的文献计量出版趋势”。我们研究了与人工智能和结石病相关的出版趋势，包括临床和外科应用以及腔内泌尿外科培训。方法通过 PubMed 上的 MeshTerms 研究，我们对 1994 年至 2023 年所有发表的“人工智能、机器学习、虚拟现实和放射组学”论文进行了全面回顾。然后，论文分为三类：A-临床（非手术）、B-临床（手术）和 C-培训论文，然后将文章分配到 3 个时期：时期 1（1994-2003）、时期 2 （2004-2013），第三期（2014-2023）。结果 343 篇论文被注意到（组 A-129、B-163 和 C-51），趋势从第一阶段到第二阶段增加了 123%（p=0.009），到第三阶段则增加了 453%（p =0.003）。A、B 和 C 组从第二阶段到第三阶段的增幅分别为 476% (p=0.019)、616% (0.001) 和 185% (p<0.001)。A 组论文包括“结石特征”(+2100%；p=0.011)、“肾功能”(p=0.002)、“结石诊断”(+192%)、“结石排出预测”(+ 400%）和“生活质量”（+1000%）。B 组论文包括“URS”（+2650%，p=0.008）、“PCNL”（+600%，p=0.001）和“SWL”（+650%，p=0.018）论文数量的上升。“目标”（+453%，p<0.001）、“结果”（+850%，p=0.013）和“技术创新”（p=0.0311）的论文呈上升趋势。C 组论文包括“PCNL”（+300%，p=0.039）和“URS”（+188%，p=0.003）论文数量的上升。结论 在过去十年中，关于泌尿系结石及其子领域的出版物呈指数增长，外科和非外科临床领域以及培训也随之增加。未来腔内泌尿外科和尿石症领域与人工智能相关的增长可能会改善培训、以患者为中心的决策和临床结果。