Department of Medical Ultrasound, The Second Hospital of Anhui Medical University, Hefei 230601, Anhui Province, China.
Department of Medical Ultrasound, Minda Hospital of Hubei Minzu University, Enshi 445000, Hubei Province, China.
World J Gastroenterol. 2021 Sep 14;27(34):5715-5726. doi: 10.3748/wjg.v27.i34.5715.
Recently, increasing attention has been paid to the application of artificial intelligence (AI) to the diagnosis of diverse hepatic diseases, which comprises traditional machine learning and deep learning. Recent studies have shown the possible value of AI based data mining in predicting the incidence of hepatitis, classifying the different stages of hepatitis, diagnosing or screening for hepatitis, forecasting the progression of hepatitis, and predicting response to antiviral drugs in chronic hepatitis C patients. More importantly, AI based on radiology has been proven to be useful in predicting hepatitis and liver fibrosis as well as grading hepatocellular carcinoma (HCC) and differentiating it from benign liver tumors. It can predict the risk of vascular invasion of HCC, the risk of hepatic encephalopathy secondary to hepatitis B related cirrhosis, and the risk of liver failure after hepatectomy in HCC patients. In this review, we summarize the application of AI in hepatitis, and identify the challenges and future perspectives.
最近，人们越来越关注人工智能 (AI) 在诊断各种肝脏疾病中的应用，包括传统机器学习和深度学习。最近的研究表明，基于人工智能的数据挖掘在预测肝炎的发生、分类肝炎的不同阶段、诊断或筛查肝炎、预测肝炎的进展以及预测慢性丙型肝炎患者对抗病毒药物的反应方面具有潜在价值。更重要的是，基于影像学的人工智能已被证明可用于预测肝炎和肝纤维化，以及对肝细胞癌 (HCC) 进行分级和与良性肝脏肿瘤进行区分。它可以预测 HCC 的血管侵犯风险、乙型肝炎相关肝硬化继发肝性脑病的风险以及 HCC 患者肝切除术后肝功能衰竭的风险。在这篇综述中，我们总结了人工智能在肝炎中的应用，并确定了挑战和未来展望。
