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ORCIDLi Shen 0001
Person information
- affiliation: University of Pennsylvania, Philadelphia, USA
- affiliation (2007 - 2017): Indiana University School of Medicine, Indianapolis, IN, USA
- affiliation (2004 - 2007): University of Massachusetts Dartmouth, MA, USA
- affiliation (PhD 2004): Dartmouth College, Hanover, NH, USA
Other persons with the same name
- Li Shen — disambiguation page
- Li Shen 0002 — Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China
- Li Shen 0003 — Institute for Infocomm Research, Singapore
- Li Shen 0004
![[0000-0003-4638-3329]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-4638-3329")
— Southwest Jiaotong University, Faculty of Geosciences and Environmental Engineering, Chengdu, China (and 1 more) - Li Shen 0005 — Alibaba Group, Beijing, China (and 3 more)
- Li Shen 0006 — Osaka University, Graduate School of Information Science and Technology, Japan
- Li Shen 0007 — National University of Defense Technology, School of Computer, Changsha, Hunan, China
- Li Shen 0008 — Tencent, Shenzhen, China (and 1 more)
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2020 – today
- 2023
[j71]Jingxuan Bao, Changgee Chang, Qiyiwen Zhang, Andrew J. Saykin, Li Shen, Qi Long:
Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis. Briefings Bioinform. 24(2) (2023)- [i10]Zhijian Yang, Junhao Wen, Ahmed Abdulkadir, Yuhan Cui, Güray Erus, Elizabeth Mamourian, Randa Melhem, Dhivya Srinivasan, Sindhuja T. Govindarajan, Jiong Chen, Mohamad Habes, Colin L. Masters, Paul Maruff, Jurgen Fripp, Luigi Ferrucci, Marilyn S. Albert, Sterling C. Johnson, John C. Morris, Pamela LaMontagne, Daniel S. Marcus, Tammie L. S. Benzinger, David A. Wolk, Li Shen, Jingxuan Bao, Susan M. Resnick, Haochang Shou, Ilya M. Nasrallah, Christos Davatzikos:
Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering. CoRR abs/2301.10772 (2023) - [i9]Reza Shirkavand, Liang Zhan, Heng Huang, Li Shen, Paul M. Thompson:
Incomplete Multimodal Learning for Complex Brain Disorders Prediction. CoRR abs/2305.16222 (2023) - 2022
- [j70]Chong Jin, Brian Lee, Li Shen, Qi Long:
Integrating multi-omics summary data using a Mendelian randomization framework. Briefings Bioinform. 23(6) (2022) - [j69]Hung Mai, Jingxuan Bao, Paul M. Thompson, Dokyoon Kim, Li Shen:
Identifying genes associated with brain volumetric differences through tissue specific transcriptomic inference from GWAS summary data. BMC Bioinform. 23-S(3): 398 (2022) - [j68]Yixue Feng, Mansu Kim, Xiaohui Yao, Kefei Liu, Qi Long, Li Shen:
Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment. BMC Bioinform. 23-S(3): 402 (2022) - [j67]Peng Yang, Cheng Zhao, Qiong Yang, Zheng Wei, Xiaohua Xiao, Li Shen, Tianfu Wang, Baiying Lei, Ziwen Peng:
Diagnosis of obsessive-compulsive disorder via spatial similarity-aware learning and fused deep polynomial network. Medical Image Anal. 75: 102244 (2022) - [j66]Mansu Kim, Eun Jeong Min, Kefei Liu, Jingwen Yan, Andrew J. Saykin, Jason H. Moore, Qi Long, Li Shen:
Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. Medical Image Anal. 76: 102297 (2022) - [c113]Diego Machado Reyes, Mansu Kim, Hanqing Chao, Li Shen, Pingkun Yan:
Connectome transformer with anatomically inspired attention for Parkinson's diagnosis. BCB 2022: 35:1-35:4 - [c112]Diego Machado Reyes, Mansu Kim, Hanqing Chao, Juergen Hahn, Li Shen, Pingkun Yan:
Genomics transformer for diagnosing Parkinson's disease. BHI 2022: 1-4 - [c111]Jiahang Sha, Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Yuhan Cui, Junhao Wen, Christos Davatzikos, Jason H. Moore, Andrew J. Saykin, Qi Long, Li Shen:
Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. BIBM 2022: 541-548 - [c110]Jun Yu, Benjamin Zalatan, Yong Chen, Li Shen, Lifang He:
Tensor-Based Multi-Modal Multi-Target Regression for Alzheimer's Disease Prediction. BIBM 2022: 639-646 - [c109]Zexuan Wang, Wenxi Yang, Katharine Ryan, Sumita Garai, Benjamin M. Auerbach, Li Shen:
Using Optimal Transport to Improve Spherical Harmonic Quantification of Complex Biological Shapes. BIBM 2022: 1255-1261 - [c108]Frederick Xu, Sumita Garai, Duy Duong-Tran, Andrew J. Saykin, Yize Zhao, Li Shen:
Consistency of Graph Theoretical Measurements of Alzheimer's Disease Fiber Density Connectomes Across Multiple Parcellation Scales. BIBM 2022: 1323-1328 - [c107]Daniele Pala, Brian Lee, Xia Ning, Dokyoon Kim, Li Shen:
Mediation Analysis and Mixed-Effects Models for the Identification of Stage-specific Imaging Genetics Patterns in Alzheimer's Disease. BIBM 2022: 2667-2673 - [c106]Houliang Zhou, Lifang He, Yu Zhang, Li Shen, Brian Chen:
Interpretable Graph Convolutional Network Of Multi-Modality Brain Imaging For Alzheimer's Disease Diagnosis. ISBI 2022: 1-5 - [c105]Houliang Zhou, Yu Zhang, Brian Y. Chen, Li Shen, Lifang He:
Sparse Interpretation of Graph Convolutional Networks for Multi-modal Diagnosis of Alzheimer's Disease. MICCAI (8) 2022: 469-478 - [c104]Honghui Shang, Li Shen, Yi Fan, Zhiqian Xu, Chu Guo, Jie Liu, Wenhao Zhou, Huan Ma, Rongfen Lin, Yuling Yang, Fang Li, Zhuoya Wang, Yunquan Zhang, Zhenyu Li:
Large-Scale Simulation of Quantum Computational Chemistry on a New Sunway Supercomputer. SC 2022: 14:1-14:14 - [i8]Houliang Zhou, Lifang He, Yu Zhang, Li Shen, Brian Chen:
Interpretable Graph Convolutional Network of Multi-Modality Brain Imaging for Alzheimer's Disease Diagnosis. CoRR abs/2204.13188 (2022) - [i7]Jun Yu, Zhaoming Kong, Liang Zhan, Li Shen, Lifang He:
Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis. CoRR abs/2209.11372 (2022) - 2021
- [j65]Mansu Kim, Jingxuan Bao, Kefei Liu, Bo-yong Park, Hyunjin Park, Jae Young Baik, Li Shen:
A structural enriched functional network: An application to predict brain cognitive performance. Medical Image Anal. 71: 102026 (2021) - [j64]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Li Shen, Heng Huang:
Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions. IEEE Trans. Biomed. Eng. 68(11): 3336-3346 (2021) - [j63]Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Lei Guo, Li Shen:
Multi-Task Sparse Canonical Correlation Analysis with Application to Multi-Modal Brain Imaging Genetics. IEEE ACM Trans. Comput. Biol. Bioinform. 18(1): 227-239 (2021) - [j62]Meiling Wang, Wei Shao, Xiaoke Hao, Li Shen, Daoqiang Zhang:
Identify Consistent Cross-Modality Imaging Genetic Patterns via Discriminant Sparse Canonical Correlation Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 18(4): 1549-1561 (2021) - [c103]Huang Li, Shiaofen Fang, Joaquín Goñi, Andrew J. Saykin, Li Shen:
Interactive Visualization of Deep Learning for 3D Brain Data Analysis. ICCI*CC 2021: 85-91 - [c102]Mansu Kim, Jaesik Kim, Jeffrey Qu, Heng Huang, Qi Long, Kyung-Ah Sohn, Dokyoon Kim, Li Shen:
Interpretable temporal graph neural network for prognostic prediction of Alzheimer's disease using longitudinal neuroimaging data. BIBM 2021: 1381-1384 - [c101]Yize Zhao, Xiwen Zhao, Mansu Kim, Jingxuan Bao, Li Shen:
A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits. MICCAI (5) 2021: 678-687 - [i6]Junhao Wen, Cynthia H. Y. Fu, Duygu Tosun, Yogasudha Veturi, Zhijian Yang, Ahmed Abdulkadir, Elizabeth Mamourian, Dhivya Srinivasan, Jingxuan Bao, Güray Erus, Haochang Shou, Mohamad Habes, Jimit Doshi, Erdem Varol, Scott R. Mackin, Aristeidis Sotiras, Yong Fan, Andrew J. Saykin, Yvette I. Sheline, Li Shen, Marylyn D. Ritchie, David A. Wolk, Marilyn S. Albert, Susan M. Resnick, Christos Davatzikos:
Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics. CoRR abs/2110.11347 (2021) - 2020
- [j61]Jason H. Moore, Ian Barnett, Mary Regina Boland, Yong Chen, George Demiris, Graciela Gonzalez-Hernandez, Daniel S. Herman, Blanca E. Himes, Rebecca A. Hubbard, Dokyoon Kim, Jeffrey S. Morris, Danielle L. Mowery, Marylyn D. Ritchie, Li Shen, Ryan J. Urbanowicz, John H. Holmes:
Ideas for how informaticians can get involved with COVID-19 research. BioData Min. 13(1): 3 (2020) - [j60]Xiaohui Yao, Shan Cong, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Jason H. Moore, Li Shen:
Regional imaging genetic enrichment analysis. Bioinform. 36(8): 2554-2560 (2020) - [j59]Lei Du, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen:
Identifying diagnosis-specific genotype-phenotype associations via joint multitask sparse canonical correlation analysis and classification. Bioinform. 36(Supplement-1): i371-i379 (2020) - [j58]Jin Li, Chenyuan Bian, Dandan Chen, Xianglian Meng, Haoran Luo, Hong Liang, Li Shen:
Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study. BMC Bioinform. 21-S(21): 535 (2020) - [j57]Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning:
Drug-drug interaction prediction based on co-medication patterns and graph matching. Int. J. Comput. Biol. Drug Des. 13(1): 36-57 (2020) - [j56]Jingwen Yan, V. Vinesh Raja, Zhi Huang, Enrico Amico, Kwangsik Nho, Shiaofen Fang, Olaf Sporns, Yu-Chien Wu, Andrew J. Saykin, Joaquín Goñi, Li Shen:
Brain-wide structural connectivity alterations under the control of Alzheimer risk genes. Int. J. Comput. Biol. Drug Des. 13(1): 58-70 (2020) - [j55]Xiaojun Chen, Weijun Hong, Feiping Nie, Joshua Zhexue Huang, Li Shen:
Enhanced Balanced Min Cut. Int. J. Comput. Vis. 128(7): 1982-1995 (2020) - [j54]Xiaoke Hao, Yongjin Bao, Yingchun Guo, Ming Yu, Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, Xiaohui Yao, Li Shen:
Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease. Medical Image Anal. 60 (2020) - [j53]Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Lei Guo, Li Shen:
Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach. Medical Image Anal. 61: 101656 (2020) - [j52]Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning:
Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data. BMC Medical Informatics Decis. Mak. 20(1): 319 (2020) - [j51]Xiaohui Yao, Tiffany Tsang, Qing Sun, Sara K. Quinney, Pengyue Zhang, Xia Ning, Lang Li, Li Shen:
Mining and visualizing high-order directional drug interaction effects using the FAERS database. BMC Medical Informatics Decis. Mak. 20-S(2): 50 (2020) - [j50]Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Li Shen, Xijia Xu, Daoqiang Zhang, Mingxia Liu:
Hierarchical Structured Sparse Learning for Schizophrenia Identification. Neuroinformatics 18(1): 43-57 (2020) - [j49]Li Shen, Paul M. Thompson:
Brain Imaging Genomics: Integrated Analysis and Machine Learning. Proc. IEEE 108(1): 125-162 (2020) - [j48]Lodewijk Brand, Kai Nichols, Hua Wang, Li Shen, Heng Huang:
Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction. IEEE Trans. Medical Imaging 39(6): 1845-1855 (2020) - [j47]Lei Du, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Li Shen:
Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method. IEEE Trans. Medical Imaging 39(11): 3416-3428 (2020) - [c100]Yingxuan Eng, Xiaohui Yao, Kefei Liu, Shannon L. Risacher, Andrew J. Saykin, Qi Long, Yize Zhao, Li Shen:
Polygenic mediation analysis of Alzheimer's disease implicated intermediate amyloid imaging phenotypes. AMIA 2020 - [c99]Yixue Feng, Mansu Kim, Xiaohui Yao, Kefei Liu, Qi Long, Li Shen:
Deep Multiview Learning to Identify Population Structure with Multimodal Imaging. BIBE 2020: 308-314 - [c98]Jingxuan Bao, Mansu Kim, Qing Sun, Anderson T. Hara, Gerardo Maupome, Li Shen:
Estimating Hard-tissue Conditions from Dental Images via Machine Learning. BIBE 2020: 315-322 - [c97]Mansu Kim, Ji Hye Won, Jisu Hong, Junmo Kwon, Hyunjin Park, Li Shen:
Deep Network-Based Feature Selection for Imaging Genetics: Application to Identifying Biomarkers for Parkinson's Disease. ISBI 2020: 1920-1923 - [c96]Jin Li, Chenyuan Bian, Dandan Chen, Xianglian Meng, Haoran Luo, Hong Liang, Li Shen:
Persistent Feature Analysis of Multimodal Brain Networks Using Generalized Fused Lasso for EMCI Identification. MICCAI (7) 2020: 44-52 - [c95]Mansu Kim, Jingxaun Bao, Kefei Liu, Bo-yong Park, Hyunjin Park, Li Shen:
Structural Connectivity Enriched Functional Brain Network Using Simplex Regression with GraphNet. MLMI@MICCAI 2020: 292-302 - [c94]Peng Yang, Qiong Yang, Wei Zheng, Li Shen, Tianfu Wang, Ziwen Peng, Baiying Lei:
Spatial Similarity-Aware Learning and Fused Deep Polynomial Network for Detection of Obsessive-Compulsive Disorder. MICCAI (7) 2020: 603-612 - [c93]Lodewijk Brand, Kai Nichols, Hua Wang, Heng Huang, Li Shen:
Predicting Longitudinal Outcomes of Alzheimer's Disease via a Tensor-Based Joint Classification andRegression Model. PSB 2020: 7-18 - [i5]Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning:
Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. CoRR abs/2002.07699 (2020) - [i4]Kefei Liu, Qi Long, Li Shen:
Grouping effects of sparse CCA models in variable selection. CoRR abs/2008.03392 (2020)
2010 – 2019
- 2019
- [j46]Lei Du, Kefei Liu, Lei Zhu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen:
Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort. Bioinform. 35(14): i474-i483 (2019) - [j45]Kefei Liu, Li Shen, Hui Jiang:
Joint between-sample normalization and differential expression detection through ℓ 0-regularized regression. BMC Bioinform. 20-S(16): 593:1-593:16 (2019) - [j44]Kefei Liu, Jieping Ye, Yang Yang, Li Shen, Hui Jiang:
A Unified Model for Joint Normalization and Differential Gene Expression Detection in RNA-Seq Data. IEEE ACM Trans. Comput. Biol. Bioinform. 16(2): 442-454 (2019) - [j43]Xiaoke Hao, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Jintai Yu, Huifu Wang, Lan Tan, Li Shen, Daoqiang Zhang:
Identifying Candidate Genetic Associations with MRI-Derived AD-Related ROI via Tree-Guided Sparse Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 16(6): 1986-1996 (2019) - [j42]Danai Chasioti, Xiaohui Yao, Pengyue Zhang, Samuel Lerner, Sara K. Quinney, Xia Ning, Lang Li, Li Shen:
Mining Directional Drug Interaction Effects on Myopathy Using the FAERS Database. IEEE J. Biomed. Health Informatics 23(5): 2156-2163 (2019) - [c92]Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning:
Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. BHI 2019: 1-4 - [c91]Xiaohui Yao, Shan Cong, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Jason H. Moore, Li Shen:
Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis. BHI 2019: 1-4 - [c90]Moo K. Chung, Shih-Gu Huang, Andrey Gritsenko, Li Shen, Hyekyoung Lee:
Statistical Inference on the Number of Cycles in Brain Networks. ISBI 2019: 113-116 - [c89]Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen:
Diagnosis Status Guided Brain Imaging Genetics Via Integrated Regression And Sparse Canonical Correlation Analysis. ISBI 2019: 356-359 - [c88]Moo K. Chung, Linhui Xie, Shih-Gu Huang, Yixian Wang, Jingwen Yan, Li Shen:
Rapid Acceleration of the Permutation Test via Transpositions. CNI@MICCAI 2019: 42-53 - [c87]Bo Peng, Zhiyun Ren, Xiaohui Yao, Kefei Liu, Andrew J. Saykin, Li Shen, Xia Ning:
Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank. MBIA/MFCA@MICCAI 2019: 139-148 - [c86]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Heng Huang, Li Shen:
Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments over Progressions. MICCAI (4) 2019: 140-148 - [c85]Ayagoz Mussabayeva, Maxim Pisov, Anvar Kurmukov, Alexey Kroshnin, Yulia Denisova, Li Shen, Shan Cong, Lei Wang, Boris Gutman:
Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models. MBIA/MFCA@MICCAI 2019: 151-161 - [c84]Lei Du, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen:
A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics. MICCAI (4) 2019: 447-455 - [e5]Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang C. Joshi, Mads Nielsen, Tom Fletcher, Stanley Durrleman, Stefan Sommer:
Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy - 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11846, Springer 2019, ISBN 978-3-030-33225-9 [contents] - [i3]Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning:
Drug-drug interaction prediction based on co-medication patterns and graph matching. CoRR abs/1902.08675 (2019) - 2018
- [j41]Jingwen Yan, Shannon L. Risacher, Li Shen, Andrew J. Saykin:
Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data. Briefings Bioinform. 19(6): 1370-1381 (2018) - [j40]Lei Du, Kefei Liu, Tuo Zhang, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen:
A novel SCCA approach via truncated ℓ1-norm and truncated group lasso for brain imaging genetics. Bioinform. 34(2): 278-285 (2018) - [j39]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) - [j38]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) - [j37]Wen-Hao Chiang, Titus Schleyer, Li Shen, Lang Li, Xia Ning:
Pattern Discovery from High-Order Drug-Drug Interaction Relations. J. Heal. Informatics Res. 2(3): 272-304 (2018) - [j36]Bob Zigon, Huang Li, Xiaohui Yao, Shiaofen Fang, Mohammad Al Hasan, Jingwen Yan, Jason H. Moore, Andrew J. Saykin, Li Shen:
GPU Accelerated Browser for Neuroimaging Genomics. Neuroinformatics 16(3-4): 393-402 (2018) - [c83]Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen:
Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics. BIBM 2018: 356-361 - [c82]Kefei Liu, Li Shen, Hui Jian:
A Unified Model for Robust Differential Expression Analysis of RNA-Seq Data. BIBM 2018: 437-442 - [c81]Huang Li, Shiaofen Fang, Snehasis Mukhopadhyay, Andrew J. Saykin, Li Shen:
Interactive Machine Learning by Visualization: A Small Data Solution. IEEE BigData 2018: 3513-3521 - [c80]Jingwen Yan, Kefei Liu, Huang Lv, Enrico Amico, Shannon L. Risacher, Yu-Chien Wu, Shiaofen Fang, Olaf Sporns, Andrew J. Saykin, Joaquín Goñi, Li Shen:
Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model. ISBI 2018: 6-9 - [c79]Lyujian Lu, Hua Wang, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning. ISBI 2018: 545-548 - [c78]Kai Liu, Hua Wang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis. ISBI 2018: 1402-1405 - [c77]Linhui Xie, Enrico Amico, Paul Salama, Yu-Chien Wu, Shiaofen Fang, Olaf Sporns, Andrew J. Saykin, Joaquín Goñi, Jingwen Yan, Li Shen:
Heritability Estimation of Reliable Connectomic Features. CNI@MICCAI 2018: 58-66 - [c76]Ayagoz Mussabayeva, Alexey Kroshnin, Anvar Kurmukov, Yulia Denisova, Li Shen, Shan Cong, Lei Wang, Boris A. Gutman:
Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms. ShapeMI@MICCAI 2018: 160-168 - [c75]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 - [c74]Heng Huang, Li Shen, Paul M. Thompson, Kun Huang, Junzhou Huang, Lin Yang:
Session introduction. PSB 2018: 304-306 - [e4]Danail Stoyanov, Zeike Taylor, Enzo Ferrante, Adrian V. Dalca, Anne L. Martel, Lena Maier-Hein, Sarah Parisot, Aristeidis Sotiras, Bartlomiej W. Papiez, Mert R. Sabuncu, Li Shen:
Graphs in Biomedical Image Analysis - and - Integrating Medical Imaging and Non-Imaging Modalities - Second International Workshop, GRAIL 2018 - and - First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science 11044, Springer 2018, ISBN 978-3-030-00688-4 [contents] - [i2]Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning:
Drug Recommendation toward Safe Polypharmacy. CoRR abs/1803.03185 (2018) - [i1]Ayagoz Mussabayeva, Alexey Kroshnin, Anvar Kurmukov, Yulia Dodonova, Li Shen, Shan Cong, Lei Wang, Boris A. Gutman:
Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms. CoRR abs/1808.04439 (2018) - 2017
- [j35]Xiaoke Hao, Chanxiu Li, Jingwen Yan, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Daoqiang Zhang:
Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis. Bioinform. 33(14): i341-i349 (2017) - [j34]Xiaohui Yao, Jingwen Yan, Kefei Liu, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Casey S. Greene, Jason H. Moore, Andrew J. Saykin, Li Shen:
Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules. Bioinform. 33(20): 3250-3257 (2017) - [j33]Xiaohui Yao, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Two-dimensional enrichment analysis for mining high-level imaging genetic associations. Brain Informatics 4(1): 27-37 (2017) - [j32]Huang Li, Shiaofen Fang, Joey A. Contreras, John D. West, Shannon L. Risacher, Yang Wang, Olaf Sporns, Andrew J. Saykin, Joaquín Goñi, Li Shen:
Brain explorer for connectomic analysis. Brain Informatics 4(4): 253-269 (2017) - [c73]Huang Li, Shiaofen Fang, Bob Zigon, Olaf Sporns, Andrew J. Saykin, Joaquín Goñi, Li Shen:
BECA: A Software Tool for Integrated Visualization of Human Brain Data. BI 2017: 285-291 - [c72]Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Jason H. Moore, Andrew J. Saykin, Li Shen:
Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules. ICASSP 2017: 6170-6174 - [c71]Xia Ning, Titus Schleyer, Li Shen, Lang Li:
Pattern Discovery from Directional High-Order Drug-Drug Interaction Relations. ICHI 2017: 154-162 - [c70]Xia Ning, Li Shen, Lang Li:
Predicting High-Order Directional Drug-Drug Interaction Relations. ICHI 2017: 556-561 - [c69]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 - [c68]Lei Du, Tuo Zhang, Kefei Liu, Jingwen Yan, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Junwei Han, Lei Guo, Li Shen:
Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach. IPMI 2017: 543-555 - [c67]Yuming Huang, Lei Du, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen:
A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics. GRAIL/MFCA/MICGen@MICCAI 2017: 210-219 - [c66]Kefei Liu, Xiaohui Yao, Jingwen Yan, Danai Chasioti, Shannon L. Risacher, Kwangsik Nho, Andrew J. Saykin, Li Shen:
Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm. GRAIL/MFCA/MICGen@MICCAI 2017: 220-229 - [c65]Li Shen, Lee A. D. Cooper:
Session Introduction. PSB 2017: 51-57 - [c64]