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20201209何勇:Simultaneous Differential Network Analysis and Classification for Matrix-variate Data with Application to Brain Connectivity
时间:2020-12-04

报告时间:2020年12月9日下午14:30

报告形式:腾讯会议

报告嘉宾:腾讯会议

报告主题:Simultaneous Differential Network Analysis and Classification for Matrix-variate Data with Application to Brain Connectivity


报告摘要


Growing evidence has shown that the brain connectivity network experiences alterations for complex diseases such as Alzheimer`s disease. Network comparison, also known as differential network analysis, is thus particularly powerful to reveal the disease pathologies and identify clinical biomarkers for medical diagnoses (classification). Data from neurophysiological measurements are multi-dimensional and in matrix-form. Naive vectorization method is not sufficient as it ignores the structural information within the matrix.  In the article, we adopt the Kronecker product covariance matrix framework to capture both spatial and temporal correlations of the matrix-variate data while the temporal covariance matrix is treated as a nuisance parameter. By recognizing that the strengths of network connections may vary across subjects, we develop an ensemble-learning procedure, which identifies the differential interaction patterns of brain regions between the case group and the control group and conducts medical diagnosis (classification) of the disease simultaneously. Thorough simulation studies are conducted to assess the performance of the proposed method. We applied the proposed procedure to functional connectivity analysis of fMRI dataset related with Alzheimer`s disease. The hub nodes and differential interaction patterns identified are consistent with existing experimental studies, and satisfactory out-of-sample classification performance is achieved for medical diagnosis of Alzheimer`s disease. An R package “SDNCMV” for implementation is available at https://github.com/heyongstat/SDNCMV.


个人简介


何勇,山东大学金融研究院,研究员;山东大学学士,复旦大学博士,师从张新生教授;从事金融计量统计、生物统计以及机器学习等方面的研究,在国际统计学权威期刊 Biometrics, Journal of Business and Economic Statistics, Bioinformatics, Statistics in Medicine, Journal of Multivariate Analysis、中国科学:数学等发表研究论文20余篇;主持国家自然科学基金一项、山东省自然科学基金等省部级课题三项。担任美国数学评论评论员,山东省大数据研究会理事及Biometrics, JRSSC等多个国际知名学术期刊匿名审稿人。



主持人简介


李扬,中国人民大学统计学院教授、博士生导师,副院长、统计咨询研究中心主任;国际统计学会推选会员、中国商业统计学会副会长、国际生物统计学会中国分会青年理事、北京生物医学统计与数据管理研究会监事长。主要从事相关型数据分析、模型选择与不确定性评价、潜变量建模、临床试验设计等领域研究,承担国家自然科学基金面上项目、全国统计科学研究重大项目等科研项目二十余项,发表JAMA IM、Biometrics、Biostatistics、统计研究等国内外期刊研究论文五十余篇。




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