Zhang Deyu, Wu Chang, Yang Zhenghui, Yin Hua, Liu Yue, Li Wanshun, Huang Haojie, Jin Zhendong
Department of Gastroenterology, Changhai hospital, Naval Medical University, Shanghai 200433, China.
Department of Gastroenterology, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
Endosc Ultrasound. 2024 Mar-Apr;13(2):65-75. doi: 10.1097/eus.0000000000000053. Epub 2024 Apr 10.
Artificial intelligence (AI) is an epoch-making technology, among which the 2 most advanced parts are machine learning and deep learning algorithms that have been further developed by machine learning, and it has been partially applied to assist EUS diagnosis. AI-assisted EUS diagnosis has been reported to have great value in the diagnosis of pancreatic tumors and chronic pancreatitis, gastrointestinal stromal tumors, esophageal early cancer, biliary tract, and liver lesions. The application of AI in EUS diagnosis still has some urgent problems to be solved. First, the development of sensitive AI diagnostic tools requires a large amount of high-quality training data. Second, there is overfitting and bias in the current AI algorithms, leading to poor diagnostic reliability. Third, the value of AI still needs to be determined in prospective studies. Fourth, the ethical risks of AI need to be considered and avoided.
人工智能(AI)是一项具有划时代意义的技术,其中最先进的两个部分是机器学习和深度学习算法,它们通过机器学习得到了进一步发展,并且已部分应用于辅助超声内镜(EUS)诊断。据报道,人工智能辅助超声内镜诊断在胰腺肿瘤、慢性胰腺炎、胃肠道间质瘤、食管早期癌、胆道和肝脏病变的诊断中具有重要价值。人工智能在超声内镜诊断中的应用仍有一些亟待解决的问题。首先,开发灵敏的人工智能诊断工具需要大量高质量的训练数据。其次,当前的人工智能算法存在过拟合和偏差问题,导致诊断可靠性较差。第三,人工智能的价值仍需在前瞻性研究中加以确定。第四,需要考虑并避免人工智能的伦理风险。