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

doi:10.3877/cma.j.issn.1674-3253.2025.03.001

Abstract

Abstract:

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.

Key words: Bladder cancer, Artificial intelligence, Urinalysis, Non-invasive diagnosis

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

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