Application and Development of Artificial Intelligence in A Pathological Study of Urinary System Tumors
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摘要:
2020年全球癌症统计数据显示，泌尿系肿瘤发病人数约占癌症总人数的13%。目前泌尿系肿瘤的诊断方法以影像学检查、内窥镜检查和病理检查为主。作为肿瘤诊断的“金标准”，病理检查存在病理医生缺乏、操作时间长等问题。人工智能具有强大的病理图像识别和特征分析能力，可作为辅助诊断，已经在多种泌尿系肿瘤中实现了肿瘤的自动诊断、分型、分期、分级和预后预测。但人工智能仍存在诸多不足，限制了其在临床的应用。本文就人工智能及其在泌尿系肿瘤病理研究中的应用进展作一综述。
Abstract:Global Cancer Statistics for 2020 show that urinary system tumors account for approximately 13% of the total number of cancers. At present, the diagnostic methods of urinary system tumors are imaging, endoscopy, and pathological examination. As the gold standard of tumor diagnosis, pathological examination has problems such as lack of pathologists and long operation time. Artificial intelligence (AI), with a strong ability for pathology image recognition and feature analysis, can be used as an auxiliary diagnosis. It has realized automatic diagnosis, typing, staging, grading, and prognosis prediction in several urinary system tumors. However, AI still has many shortcomings, which limit its clinical application. This article will review the progress of AI and its application in the pathological study of urinary system tumors.
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Key words:
- Artificial intelligence /
- Pathology /
- Prostate cancer /
- Bladder cancer /
- Kidney cancer
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Competing interests: The authors declare that they have no competing interests.作者贡献：倪鑫淼：提纲设计，文献收集整理，论文撰写杨瑞、陈志远：论文修改刘修恒：总体策划，论文审校
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