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Development and validation of a radiomics signature for clinically significant portal hypertension in cirrhosis (CHESS1701): a prospective multicenter study.肝硬化临床显著性门静脉高压症的放射组学特征的建立和验证(CHESS1701):一项前瞻性多中心研究。
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Will the magnetic resonance imaging proton density fat fraction replace liver biopsy as the gold standard for detecting steatosis?磁共振成像质子密度脂肪分数会取代肝活检成为检测脂肪变性的金标准吗?
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Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.多参数超声弹性成像技术在显著肝纤维化中的应用:基于机器学习的分析。
Eur Radiol. 2019 Mar;29(3):1496-1506. doi: 10.1007/s00330-018-5680-z. Epub 2018 Sep 3.
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Predicting prognosis of resected hepatocellular carcinoma by radiomics analysis with random survival forest.基于随机生存森林的影像组学分析预测肝癌切除术患者预后。
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Assessment of Therapy Response to Transarterial Radioembolization for Liver Metastases by Means of Post-treatment MRI-Based Texture Analysis.通过基于治疗后MRI的纹理分析评估经动脉放射性栓塞治疗肝转移瘤的疗效。
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Decoding Tumor Biology of Colorectal Liver Metastases With Radiogenomics: A Novel Insight Into Surgical Approach Selection.利用放射基因组学解码结直肠癌肝转移的肿瘤生物学:手术方法选择的新见解
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Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study.深度学习剪切波弹性成像放射组学显著提高了慢性乙型肝炎肝纤维化评估的诊断性能:一项前瞻性多中心研究。
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基于人工智能的肝脏疾病放射组学:我们目前的进展如何?

Radiomics based on artificial intelligence in liver diseases: where we are?

作者信息

Hu Wenmo, Yang Huayu, Xu Haifeng, Mao Yilei

机构信息

Department of Liver Surgery, Peking Union Medical College Hospital, PUMC, Chinese Academy of Medical Sciences, Beijing, P. R. China.

出版信息

Gastroenterol Rep (Oxf). 2020 Apr 7;8(2):90-97. doi: 10.1093/gastro/goaa011. eCollection 2020 Apr.

DOI:10.1093/gastro/goaa011
PMID:32280468
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7136719/
Abstract

Radiomics uses computers to extract a large amount of information from different types of images, form various quantifiable features, and select relevant features using artificial-intelligence algorithms to build models, in order to predict the outcomes of clinical problems (such as diagnosis, treatment, prognosis, etc.). The study of liver diseases by radiomics will contribute to early diagnosis and treatment of liver diseases and improve survival and cure rates of liver diseases. This field is currently in the ascendant and may have great development in the future. Therefore, we summarize the progress of current research in this article and then point out the related deficiencies and the direction of future research.

摘要

放射组学利用计算机从不同类型的图像中提取大量信息,形成各种可量化特征,并使用人工智能算法选择相关特征来构建模型,以预测临床问题的结果(如诊断、治疗、预后等)。通过放射组学对肝脏疾病进行研究将有助于肝脏疾病的早期诊断和治疗,并提高肝脏疾病的生存率和治愈率。该领域目前正方兴未艾,未来可能会有很大的发展。因此,我们在本文中总结了当前研究的进展,然后指出相关不足以及未来的研究方向。