Abstract：
Recent advancements in computer-assisted diagnosis (CAD) have catalysed significant progress in pathology, particularly in the realm of urine cytopathology. This review synthesizes the latest developments and challenges in CAD for diagnosing urothelial carcinomas, addressing the limitations of traditional urinary cytology. Through a literature review, we identify and analyse CAD models and algorithms developed for urine cytopathology, highlighting their methodologies and performance metrics. We discuss the potential of CAD to improve diagnostic accuracy, efficiency and patient outcomes, emphasizing its role in streamlining workflow and reducing errors. Furthermore, CAD tools have shown potential in exploring pathological conditions, uncovering novel biomarkers and prognostic/predictive features previously unknown or unseen. Finally, we examine the practical issues surrounding the integration of CAD into clinical practice, including regulatory approval, validation and training for pathologists. Despite the promising results, challenges remain, necessitating further research and validation efforts. Overall, CAD presents a transformative opportunity to revolutionize diagnostic practices in urine cytopathology, paving the way for enhanced patient care and outcomes.
摘要：
计算机辅助诊断（CAD）的最新进展促进了病理学的重大进展，特别是在尿液细胞病理学领域。这篇综述综合了CAD诊断尿路上皮癌的最新进展和挑战。解决传统尿细胞学的局限性。通过文献综述,我们识别和分析为尿液细胞病理学开发的CAD模型和算法，强调他们的方法和性能指标。我们讨论了CAD提高诊断准确性的潜力，效率和患者结果，强调其在简化工作流程和减少错误方面的作用。此外，CAD工具在探索病理状况方面显示出潜力，发现新的生物标志物和以前未知或看不见的预后/预测特征。最后,我们研究了围绕CAD融入临床实践的实际问题，包括监管部门的批准，病理学家的验证和培训。尽管结果很有希望，挑战依然存在,需要进一步的研究和验证工作。总的来说,CAD提供了一个革命性的机会，以彻底改变尿液细胞病理学的诊断实践，为加强患者护理和结果铺平道路。
