Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature
文献类型:期刊论文
作者 | Li, Yiming1![]() ![]() |
刊名 | EUROPEAN RADIOLOGY
![]() |
出版日期 | 2018-07-01 |
卷号 | 28期号:7页码:2960-2968 |
关键词 | Magnetic Resonance Imaging Genetics Biomarkers Glioma Machine Learning |
DOI | 10.1007/s00330-017-5267-0 |
文献子类 | Article |
英文摘要 | To predict ATRX mutation status in patients with lower-grade gliomas using radiomic analysis. |
WOS关键词 | IDH1 MUTATIONS ; DIFFUSE GLIOMA ; CLASSIFICATION ; EXPRESSION ; BIOMARKERS ; REVEALS ; SYSTEM ; IMAGES ; TUMORS |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
语种 | 英语 |
WOS记录号 | WOS:000434251800031 |
资助机构 | National Natural Science Foundation of China(81601452) ; Beijing Natural Science Foundation(7174295) ; National Key Research and Development Plan(2016YFC0902500) |
源URL | [http://ir.ia.ac.cn/handle/173211/22050] ![]() |
专题 | 自动化研究所_脑网络组研究中心 |
作者单位 | 1.Capital Med Univ, Beijing Neurosurg Inst, 6 Tiantanxili, Beijing 100050, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 3.Capital Med Univ, Beijing Tiantan Hosp, Dept Neuroradiol, Beijing, Peoples R China 4.Capital Med Univ, Beijing Neurosurg Inst, Neurol Imaging Ctr, Beijing, Peoples R China 5.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, 6 Tiantanxili, Beijing 100050, Peoples R China 6.Beijing Inst Brain Disorders, Ctr Brain Tumor, Beijing, Peoples R China 7.China Natl Clin Res Ctr Neurol Dis, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Yiming,Liu, Xing,Qian, Zenghui,et al. Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature[J]. EUROPEAN RADIOLOGY,2018,28(7):2960-2968. |
APA | Li, Yiming.,Liu, Xing.,Qian, Zenghui.,Sun, Zhiyan.,Xu, Kaibin.,...&Jiang, Tao.(2018).Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.EUROPEAN RADIOLOGY,28(7),2960-2968. |
MLA | Li, Yiming,et al."Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature".EUROPEAN RADIOLOGY 28.7(2018):2960-2968. |
入库方式: OAI收割
来源:自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。