Qin Feng, Yuan Jiuhong
Andrology Laboratory, Department of Urology, West China Hospital, Sichuan University, Chengdu 610041, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2020 Apr 25;37(2):230-235. doi: 10.7507/1001-5515.201910055.
Recently, artificial intelligence (AI) has been widely applied in the diagnosis and treatment of urinary diseases with the development of data storage, image processing, pattern recognition and machine learning technologies. Based on the massive biomedical big data of imaging and histopathology, many urinary system diseases (such as urinary tumor, urological calculi, urinary infection, voiding dysfunction and erectile dysfunction) will be diagnosed more accurately and will be treated more individualizedly. However, most of the current AI diagnosis and treatment are in the pre-clinical research stage, and there are still some difficulties in the wide application of AI. This review mainly summarizes the recent advances of AI in the diagnosis of prostate cancer, bladder cancer, kidney cancer, urological calculi, frequent micturition and erectile dysfunction, and discusses the future potential and existing problems.
近年来，随着数据存储、图像处理、模式识别和机器学习技术的发展，人工智能（AI）已广泛应用于泌尿系统疾病的诊断和治疗。基于海量的生物医学成像和组织病理学大数据，许多泌尿系统疾病（如泌尿系统肿瘤、泌尿系统结石、泌尿系统感染、排尿功能障碍和勃起功能障碍）将得到更准确的诊断和更个体化的治疗。然而，目前大多数人工智能诊断和治疗仍处于临床前研究阶段，人工智能的广泛应用仍存在一些困难。本文综述主要总结了人工智能在前列腺癌、膀胱癌、肾癌、泌尿系统结石、尿频和勃起功能障碍诊断方面的最新进展，并探讨了其未来潜力和存在的问题。
