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Shannon L. Risacher
- > Home > Persons > Shannon L. Risacher
Publications
- 2023
- [c42]Zixuan Wen, Jingxuan Bao, Shu Yang, Shannon L. Risacher, Andrew J. Saykin, Paul M. Thompson, Christos Davatzikos, Heng Huang, Yize Zhao, Li Shen:
Identifying Shared Neuroanatomic Architecture Between Cognitive Traits Through Multiscale Morphometric Correlation Analysis. MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI 2023: 227-240 - 2018
- [j18]Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang:
Quantitative trait loci identification for brain endophenotypes via new additive model with random networks. Bioinform. 34(17): i866-i874 (2018) - [j17]Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang:
Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model. J. Comput. Biol. 25(7): 809-824 (2018) - [c31]Lodewijk Brand, Hua Wang, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease. MICCAI (1) 2018: 555-562 - 2017
- [c28]Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang:
Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model. IPMI 2017: 198-209 - [c23]Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang:
Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model. RECOMB 2017: 287-302 - 2016
- [j11]Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method. Bioinform. 32(10): 1544-1551 (2016) - [j10]Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Structured sparse CCA for brain imaging genetics via graph OSCAR. BMC Syst. Biol. 10(S-3): 68 (2016) - 2015
- [c17]Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics. BIH 2015: 275-284 - 2014
- [j8]Jingwen Yan, Lei Du, Sungeun Kim, Shannon L. Risacher, Heng Huang, Jason H. Moore, Andrew J. Saykin, Li Shen:
Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm. Bioinform. 30(17): 564-571 (2014) - [c14]Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics. MICCAI (3) 2014: 329-336 - 2013
- [c12]De Wang, Feiping Nie, Heng Huang, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions. IPMI 2013: 536-547 - [c9]Jingwen Yan, Heng Huang, Shannon L. Risacher, Sungeun Kim, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures. MBIA 2013: 202-210 - 2012
- [j7]Hua Wang, Feiping Nie, Heng Huang, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort. Bioinform. 28(2): 229-237 (2012) - [j6]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning. Bioinform. 28(12): 127-136 (2012) - [j5]Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs. Bioinform. 28(18): 619-625 (2012) - [c7]Jingwen Yan, Shannon L. Risacher, Sungeun Kim, Jacqueline C. Simon, Taiyong Li, Jing Wan, Hua Wang, Heng Huang, Andrew J. Saykin, Li Shen:
Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning. MBIA 2012: 1-17 - [c6]Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction. NIPS 2012: 1286-1294 - 2011
- [c5]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Chris H. Q. Ding, Andrew J. Saykin, Li Shen:
Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance. ICCV 2011: 557-562 - [c3]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression. MICCAI (3) 2011: 115-123
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