.png){kind=icon}
返回
Artificial intelligence for hepatitis evaluation
.png){kind=icon}
OA
AI
DOI：10.3748/wjg.v27.i34.5715.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Machine learning
Deep learning
Radiomics
Hepatitis
Fibrosis
Hepatocellular carcinoma
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.4
论文数:
2.1W
被引数:
5.1W
机构
引用论文
Analysing interspecific associations in parasites: alternative methods and effects of sampling heterogeneity.png)
Oecologia
OecologiaIF0
PREAI
分享收藏A pH responsive fluorescent probe based on dye modified i-motif nucleic acids基于染料修饰的i-motif核酸的pH响应性荧光探针
PREAI
分享收藏Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid-enhanced Hepatobiliary Phase MR ImagesRADIOLOGY
RADIOLOGYIF15.2
PREAI
分享收藏A Kinetic Model with Ordered Cytoplasmic Dissociation for SUC1, an Arabidopsis H + /Sucrose Cotransporter Expressed in Xenopus Oocytes在非洲爪蟾卵母细胞中表达的拟南芥H/蔗糖协同转运蛋白SUC1的有序细胞质解离动力学模型
PREAI
分享收藏
查看更多内容