Liu Kun, Zhang Mingyang, Li Haoran, Wang Xianghui, Li Dongming, Liu Shuang, Yang Kun, Sun Zhenduo, Xue Linyan, Cui Zhenyu
School of Quality and Technical Supervision, Hebei University, Baoding, Hebei 071002, P.R.China.
Postdoctoral Research Station of Optical Engineering, Hebei University, Baoding, Hebei 071002, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Dec 25;38(6):1219-1228. doi: 10.7507/1001-5515.202103010.
With the rapid development of artificial intelligence technology, researchers have applied it to the diagnosis of various tumors in the urinary system in recent years, and have obtained many valuable research results. The article sorted the research status of artificial intelligence technology in the fields of renal tumors, bladder tumors and prostate tumors from three aspects: the number of papers, image data, and clinical tasks. The purpose is to summarize and analyze the research status and find new valuable research ideas in the future. The results show that the artificial intelligence model based on medical data such as digital imaging and pathological images is effective in completing basic diagnosis of urinary system tumors, image segmentation of tumor infiltration areas or specific organs, gene mutation prediction and prognostic effect prediction, but most of the models for the requirement of clinical application still need to be improved. On the one hand, it is necessary to further improve the detection, classification, segmentation and other performance of the core algorithm. On the other hand, it is necessary to integrate more standardized medical databases to effectively improve the diagnostic accuracy of artificial intelligence models and make it play greater clinical value.
随着人工智能技术的快速发展，近年来研究人员已将其应用于泌尿系统各种肿瘤的诊断，并取得了许多有价值的研究成果。文章从论文数量、图像数据和临床任务三个方面梳理了人工智能技术在肾肿瘤、膀胱肿瘤和前列腺肿瘤领域的研究现状。目的是总结分析研究现状，寻找未来新的有价值的研究思路。结果表明，基于数字成像和病理图像等医学数据的人工智能模型在完成泌尿系统肿瘤的基本诊断、肿瘤浸润区域或特定器官的图像分割、基因突变预测和预后效果预测方面是有效的，但大多数模型对于临床应用的要求仍有待提高。一方面，有必要进一步提升核心算法的检测、分类、分割等性能。另一方面，有必要整合更多标准化医学数据库，以有效提高人工智能模型的诊断准确性，使其发挥更大的临床价值。
