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中华腔镜泌尿外科杂志(电子版) ›› 2025, Vol. 19 ›› Issue (03) : 283 -287. doi: 10.3877/cma.j.issn.1674-3253.2025.03.001

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人工智能时代尿液无创检测方法在膀胱癌诊断中的应用
黄世旺1, 郄云凯1, 胡海龙1,()   
  1. 1. 300211 天津医科大学第二医院泌尿外科,天津市泌尿外科研究所
  • 收稿日期:2025-01-07 出版日期:2025-06-01
  • 通信作者: 胡海龙
  • 基金资助:
    国家自然科学基金项目(82403319)天津市教委科研计划项目(2022ZD069)天津市卫健委重点学科专项(TJWJ2022XK014)

Application of artificial intelligence in non-invasive urine-based diagnostic methods for bladder cancer

Shiwang Huang1, Yunkai Qie1, Hailong Hu1,()   

  1. 1. Department of Urology, the Second Hospital of Tianjin Medical University,Tianjin Institute of Urology, Tianjin 300211, China
  • Received:2025-01-07 Published:2025-06-01
  • Corresponding author: Hailong Hu
引用本文:

黄世旺, 郄云凯, 胡海龙. 人工智能时代尿液无创检测方法在膀胱癌诊断中的应用[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2025, 19(03): 283-287.

Shiwang Huang, Yunkai Qie, Hailong Hu. Application of artificial intelligence in non-invasive urine-based diagnostic methods for bladder cancer[J/OL]. Chinese Journal of Endourology(Electronic Edition), 2025, 19(03): 283-287.

膀胱癌是泌尿系统最常见的恶性肿瘤之一,具有高复发率和进展风险。传统尿液检测方法在敏感性和特异性方面存在局限,而人工智能(AI)的引入显著提升了诊断的准确性。本文概述了AI 技术与脱落细胞学、基因测序、蛋白质组学、代谢组学、微生物组学、DNA 甲基化及流式细胞术等尿液检测方法的结合,展示了其在膀胱癌诊断中的应用潜力,并分析了其临床推广所面临的挑战,为相关研究与临床实践提供了重要参考。

Bladder cancer is one of the most common malignant tumors of the urinary system, characterized by high recurrence rates and progression risks.Traditional urine-based diagnostic methods are limited in terms of sensitivity and specificity, whereas the introduction of artificial intelligence (AI) has significantly improved diagnostic accuracy.This article summarizes the combination of AI technology with various urine-based diagnostic techniques, including cytology,genetic sequencing, proteomics, metabolomics, microbiomics, DNA methylation, and flow cytometry, highlighting their potential applications in bladder cancer diagnosis.The challenges of clinical implementation are also discussed, providing valuable insights for further research and clinical practice.

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