Mining Flexible Multiple-Level Association Rules in All Concept Hierarchies (Extended Abstract). - Li Shen 001; Hong Shen (DEXA, 1998)

New Algorithms for Efficient Mining of Association Rules. - Li Shen 001; Hong Shen; Ling Cheng (Inf. Sci., 1999)

Mining the Most Interesting Web Access Associations. - Li Shen 001; Ling Cheng; James Ford; Fillia Makedon; Vasileios Megalooikonomou; Tilmann Steinberg (WebNet, 2000)

Fast Association Discovery in Derivative Transaction Collections. - Li Shen 001; Hong Shen; Ling Cheng; Paul Pritchard (Knowl. Inf. Syst., 2000)

MetaDL: A Digital Library of Metadata for Sensitive or Complex Research Data. - Fillia Makedon; James Ford; Li Shen 001; Tilmann Steinberg; Andrew J. Saykin; Heather Wishart; Sarantos Kapidakis (ECDL, 2002)

SCENS: A System for the Mediated Sharing of Sensitive Data. - Song Ye; Fillia Makedon; Tilmann Steinberg; Li Shen 001; James Ford; Yuhang Wang; Yan Zhao; Sarantos Kapidakis (JCDL, 2003)

Morphometric Analysis of Brain Structures for Improved Discrimination. - Li Shen 001; James Ford; Fillia Makedon; Yuhang Wang; Tilmann Steinberg; Song Ye; Andrew J. Saykin (MICCAI (2), 2003)

Hippocampal shape analysis: surface-based representation and classification. - Li Shen 001; James Ford; Fillia Makedon; Andrew J. Saykin (Image Processing, 2003)

A Spatio-temporal Multi-modal Data Management and Analysis Environment for Tracking MS Lesions. - Tilmann Steinberg; Yuhang Wang; Fillia Makedon; Li Shen 001; Andrew J. Saykin; Heather Wishart (SSDBM, 2003)

Spherical Parameterization for 3D Surface Analysis in Volumetric Images. - Li Shen 001; Fillia Makedon (ITCC (1), 2004)

Generating fuzzy semantic metadata describing spatial relations from images using the R-histogram. - Yuhang Wang; Fillia Makedon; James Ford; Li Shen 001; Dina Q. Goldin (JCDL, 2004)

Shape-based discriminative analysis of combined bilateral hippocampi using multiple object alignment. - Li Shen 001; Fillia Makedon; Andrew J. Saykin (Image Processing, 2004)

Data Brokers: Building Collections through Automated Negotiation. - Fillia Makedon; Song Ye; Sheng Zhang 004; James Ford; Li Shen 001; Sarantos Kapidakis (SETN, 2004)

A surface-based approach for classification of 3D neuroanatomic structures. - Li Shen 001; James Ford; Fillia Makedon; Andrew J. Saykin (Intell. Data Anal., 2004)

K-means+ Method for Improving Gene Selection for Classification of Microarray Data. - Heng Huang; Rong Zhang 013; Fei Xiong; Fillia Makedon; Li Shen 001; Bruce Hettleman; Justin D. Pearlman (CSB Workshops, 2005)

Surface Alignment of 3D Spherical Harmonic Models: Application to Cardiac MRI Analysis. - Heng Huang; Li Shen 001; Rong Zhang 013; Fillia Makedon; Bruce Hettleman; Justin D. Pearlman (MICCAI, 2005)

A Prediction Framework for Cardiac Resynchronization Therapy Via 4D Cardiac Motion Analysis. - Heng Huang; Li Shen 001; Rong Zhang 013; Fillia Makedon; Bruce Hettleman; Justin D. Pearlman (MICCAI, 2005)

An interactive 3D visualization and manipulation tool for effective assessment of angiogenesis and arteriogenesis using computed tomographic angiography. - Li Shen 001; Ling Gao; Zhenwu Zhuang; Ebo DeMuinck; Heng Huang; Fillia Makedon; Justin D. Pearlman (Image-Guided Procedures, 2005)

Functional analysis of cardiac MR images using SPHARM modeling. - Heng Huang; Li Shen 001; James Ford; Fillia Makedon; Rong Zhang 013; Ling Gao; Justin D. Pearlman (Image Processing, 2005)

A clustering-based approach for prediction of cardiac resynchronization therapy. - Heng Huang; Li Shen 001; Fillia Makedon; Sheng Zhang 004; Mark Greenberg; Ling Gao; Justin D. Pearlman (SAC, 2005)

A Spatio-Temporal Modeling Method for Shape Representation. - Heng Huang; Li Shen 001; Rong Zhang 013; Fillia Makedon; Justin D. Pearlman (3DPVT, 2006)

Hemispherical Harmonic Surface Description and Applications to Medical Image Analysis. - Heng Huang; Lei Zhang 002; Dimitris Samaras; Li Shen 001; Rong Zhang 013; Fillia Makedon; Justin D. Pearlman (3DPVT, 2006)

Shape Analysis and Spatio-Temporal Tracking of Mesoscale Eddies in Miami Isopycnic Coordinate Ocean Model. - Veena Moolani; Ramprasad Balasubramanian; Li Shen 001; Amit Tandon (3DPVT, 2006)

Large-Scale Modeling of Parametric Surfaces Using Spherical Harmonics. - Li Shen 001; Moo K. Chung (3DPVT, 2006)

Multi-scale Voxel-Based Morphometry Via Weighted Spherical Harmonic Representation. - Moo K. Chung; Li Shen 001; Kim M. Dalton; Richard J. Davidson (MIAR, 2006)

Spatio-temporal analysis tool for modeling pulmonary nodules in MR images. - Li Shen 001; Heng Huang; James Ford; Chia-Hsin Lu; Ling Gao; Wei Zheng 009; Fillia Makedon; Justin D. Pearlman (Image-Guided Procedures, 2006)

Fast surface alignment for cardiac spatio-temporal modeling: application to ischemic cardiac shape modeling. - Heng Huang; Li Shen 001; Rong Zhang 013; Fillia Makedon; Bruce Hettleman; Justin D. Pearlman (Image Processing, 2006)

Spherical mapping for processing of 3D closed surfaces. - Li Shen 001; Fillia Makedon (Image Vis. Comput., 2006)

Morphometric Analysis of Hippocampal Shape in Mild Cognitive Impairment: An Imaging Genetics Study. - Li Shen 001; Andrew J. Saykin; Moo K. Chung; Heng Huang (BIBE, 2007)

Efficient Registration of 3D SPHARM Surfaces. - Li Shen 001; Heng Huang; Fillia Makedon; Andrew J. Saykin (CRV, 2007)

Surface Harmonics for Shape Modeling. - Heng Huang; Li Shen 001 (ICIP (2), 2007)

Three-dimensional Models for Cardiac Bioelectricity Simulation: Cell to Organ. - Heng Huang; Li Shen 001; Nha Nguyen (Simul., 2007)

A Novel Surface Registration Algorithm With Biomedical Modeling Applications. - Heng Huang; Li Shen 001; Rong Zhang 013; Fillia Makedon; Andrew J. Saykin; Justin D. Pearlman (IEEE Trans. Inf. Technol. Biomed., 2007)

Weighted Fourier Series Representation and Its Application to Quantifying the Amount of Gray Matter. - Moo K. Chung; Kim M. Dalton; Li Shen 001; Alan C. Evans; Richard J. Davidson (IEEE Trans. Medical Imaging, 2007)

Data synthesis and tool development for exploring imaging genomic patterns. - Sungeun Kim; Li Shen 001; Andrew J. Saykin; John D. West (CIBCB, 2009)

Fourier method for large-scale surface modeling and registration. - Li Shen 001; Sungeun Kim; Andrew J. Saykin (Comput. Graph., 2009)

Mining 3D Shape Data for Morphometric Pattern Discovery. - Li Shen 001; Fillia Makedon (Encyclopedia of Data Warehousing and Mining, 2009)

A Framework for 3D Analysis of Facial Morphology in Fetal Alcohol Syndrome. - Jing Wan; Li Shen 001; Shiaofen Fang; Jason McLaughlin; Ilona Autti-Rämö; Åse Fagerlund; Edward P. Riley; H. Eugene Hoyme; Elizabeth S. Moore; Tatiana Foroud (MIAR, 2010)

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction. - Li Shen 001; Yuan (Alan) Qi; Sungeun Kim; Kwangsik Nho; Jing Wan; Shannon L. Risacher; Andrew J. Saykin (MICCAI (3), 2010)

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort. - Li Shen 001; Sungeun Kim; Shannon L. Risacher; Kwangsik Nho; Shanker Swaminathan; John D. West; Tatiana Foroud; Nathan Pankratz; Jason H. Moore; Chantel D. Sloan; Matthew J. Huentelman; David W. Craig; et al. (NeuroImage, 2010)

Voxelwise genome-wide association study (vGWAS). - Jason L. Stein; Xue Hua; Suh Lee; April J. Ho; Alex D. Leow; Arthur W. Toga; Andrew J. Saykin; Li Shen 001; Tatiana Foroud; Nathan Pankratz; Matthew J. Huentelman; David W. Craig; et al. (NeuroImage, 2010)

Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's disease. - Jason L. Stein; Xue Hua; Jonathan H. Morra; Suh Lee; Derrek P. Hibar; April J. Ho; Alex D. Leow; Arthur W. Toga; Jae Hoon Sul; Hyun Min Kang; Eleazar Eskin; Andrew J. Saykin; et al. (NeuroImage, 2010)

Age-related neuroinflammation in non-demented elderly adults: Preliminary findings with the TSPO ligand [11C]PBR28. - Karmen K. Yoder; Shannon L. Risacher; Tamiko R. MaGee; Brenna C. McDonald; Qi-Huang Zheng; Min Wang; Bruce H. Mock; John D. West; Li Shen 001; Gary D. Hutchins; Andrew J. Saykin (NeuroImage, 2010)

Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance. - Hua Wang 007; Feiping Nie 001; Heng Huang; Shannon L. Risacher; Chris H. Q. Ding; Andrew J. Saykin; Li Shen 001 (ICCV, 2011)

Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net. - Li Shen 001; Sungeun Kim; Yuan (Alan) Qi; Mark Inlow; Shanker Swaminathan; Kwangsik Nho; Jing Wan; Shannon L. Risacher; Leslie M. Shaw; John Q. Trojanowski; Michael W. Weiner; Andrew J. Saykin (MBIA, 2011)

Hippocampal Surface Mapping of Genetic Risk Factors in AD via Sparse Learning Models. - Jing Wan; Sungeun Kim; Mark Inlow; Kwangsik Nho; Shanker Swaminathan; Shannon L. Risacher; Shiaofen Fang; Michael W. Weiner; Mirza Faisal Beg; Lei Wang 032; Andrew J. Saykin; Li Shen 001 (MICCAI (2), 2011)

Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression. - Hua Wang 007; Feiping Nie 001; Heng Huang; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (MICCAI (3), 2011)

Voxelwise gene-wide association study (vGeneWAS): Multivariate gene-based association testing in 731 elderly subjects. - Derrek P. Hibar; Jason L. Stein; Omid Kohannim; Neda Jahanshad; Andrew J. Saykin; Li Shen 001; Sungeun Kim; Nathan Pankratz; Tatiana Foroud; Matthew J. Huentelman; Steven G. Potkin; Clifford R. Jack Jr.; et al. (NeuroImage, 2011)

Regional reproducibility of pulsed arterial spin labeling perfusion imaging at 3T. - Yang Wang; Andrew J. Saykin; Josef Pfeuffer; Chen Lin; Kristine M. Mosier; Li Shen 001; Sungeun Kim; Gary D. Hutchins (NeuroImage, 2011)

Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease. - Jing Wan; Zhilin Zhang 002; Jingwen Yan; Taiyong Li; Bhaskar D. Rao; Shiaofen Fang; Sungeun Kim; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (CVPR, 2012)

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning. - Jingwen Yan; Shannon L. Risacher; Sungeun Kim; Jacqueline C. Simon; Taiyong Li; Jing Wan; Hua Wang 007; Heng Huang; Andrew J. Saykin; Li Shen 001 (MBIA, 2012)

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction. - Hua Wang 007; Feiping Nie 001; Heng Huang; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (NIPS, 2012)

Pattern Visualization of Human Connectome Data. - Yishi Guo; Yang Wang; Shiaofen Fang; Hongyang Chao; Andrew J. Saykin; Li Shen 001 (EuroVis (Short Papers), 2012)

Principles of Computational Modeling in NeuroscienceDavid Sterratt, Bruce Graham, Andrew Gillies and David Willshaw. - Li Shen 001 (Briefings Bioinform., 2012)

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort. - Hua Wang 007; Feiping Nie 001; Heng Huang; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (Bioinform., 2012)

Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning. - Hua Wang 007; Feiping Nie 001; Heng Huang; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (Bioinform., 2012)

From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs. - Hua Wang 007; Feiping Nie 001; Heng Huang; Jingwen Yan; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (Bioinform., 2012)

A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort. - Shashwath A. Meda; Balaji Narayanan 002; Jingyu Liu 001; Nora I. Perrone-Bizzozero; Michael C. Stevens 001; Vince D. Calhoun; David C. Glahn; Li Shen 001; Shannon L. Risacher; Andrew J. Saykin; Godfrey D. Pearlson (NeuroImage, 2012)

Erratum to "A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's Disease in the ADNI cohort" [Neuroimage 60/3(2012) 1608-1621]. - Shashwath A. Meda; Balaji Narayanan 002; Jingyu Liu 001; Nora I. Perrone-Bizzozero; Michael C. Stevens 001; Vince D. Calhoun; David C. Glahn; Li Shen 001; Shannon L. Risacher; Andrew J. Saykin; Godfrey D. Pearlson (NeuroImage, 2012)

Exploring Interestingness in a Computational Evolution System for the Genome-Wide Genetic Analysis of Alzheimer's Disease. - Jason H. Moore; Douglas P. Hill; Andrew J. Saykin; Li Shen 001 (GPTP, 2013)

Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions. - De Wang; Feiping Nie 001; Heng Huang; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (IPMI, 2013)

Genetic Clustering on the Hippocampal Surface for Genome-Wide Association Studies. - Derrek P. Hibar; Sarah E. Medland; Jason L. Stein; Sungeun Kim; Li Shen 001; Andrew J. Saykin; Greig I. de Zubicaray; Katie McMahon; Grant W. Montgomery; Nicholas G. Martin; Margaret J. Wright; Srdjan Djurovic; et al. (MICCAI (2), 2013)

A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis. - Heng Huang; Jingwen Yan; Feiping Nie 001; Jin Huang; Weidong Cai 001; Andrew J. Saykin; Li Shen 001 (MICCAI (2), 2013)

A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI). - Dokyoon Kim; Sungeun Kim; Shannon L. Risacher; Li Shen 001; Marylyn D. Ritchie; Michael W. Weiner; Andrew J. Saykin; Kwangsik Nho (MBIA, 2013)

PARP1 Gene Variation and Microglial Activity on [11C]PBR28 PET in Older Adults at Risk for Alzheimer's Disease. - Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Mark Inlow; Shanker Swaminathan; Karmen K. Yoder; Li Shen 001; John D. West; Brenna C. McDonald; Eileen F. Tallman; Gary D. Hutchins; James W. Fletcher; et al. (MBIA, 2013)

Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures. - Jingwen Yan; Heng Huang; Shannon L. Risacher; Sungeun Kim; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (MBIA, 2013)

Interactive object extraction by merging regions with k-global maximal similarity. - Taiyong Li; Zhilong Xie; Jiang Wu; Jingwen Yan; Li Shen 001 (Neurocomputing, 2013)

Data synthesis and method evaluation for brain imaging genetics. - Jinhua Sheng; Sungeun Kim; Jingwen Yan; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (ISBI, 2014)

Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning. - Jingwen Yan; Heng Huang; Sungeun Kim; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (ISBI, 2014)

A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics. - Lei Du 001; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Heng Huang; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (MICCAI (3), 2014)

Human Connectome Module Pattern Detection Using a New Multi-graph MinMax Cut Model. - De Wang; Yang Wang; Feiping Nie 001; Jingwen Yan; Tom Weidong Cai; Andrew J. Saykin; Li Shen 001; Heng Huang (MICCAI (3), 2014)

Building a surface atlas of hippocampal subfields from MRI scans using FreeSurfer, FIRST and SPHARM. - Shan Cong; Maher E. Rizkalla; Eliza Y. Du; John D. West; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (MWSCAS, 2014)

Accelerating Sparse Canonical Correlation Analysis for Large Brain Imaging Genetics Data. - Jingwen Yan; Hui Zhang 006; Lei Du 001; Eric A. Wernert; Andrew J. Saykin; Li Shen 001 (XSEDE, 2014)

Computational genetics analysis of grey matter density in Alzheimer's disease. - Amanda L. Zieselman; Jonathan M. Fisher; Ting Hu 001; Peter C. Andrews; Casey S. Greene; Li Shen 001; Andrew J. Saykin; Jason H. Moore (BioData Min., 2014)

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm. - Jingwen Yan; Lei Du 001; Sungeun Kim; Shannon L. Risacher; Heng Huang; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Bioinform., 2014)

Improving protein order-disorder classification using charge-hydropathy plots. - Fei Huang; Christopher J. Oldfield; Bin Xue; Wei-Lun Hsu; Jingwei Meng; Xiaowen Liu; Li Shen 001; Pedro Romero; Vladimir N. Uversky; A. Keith Dunker (BMC Bioinform., 2014)

Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning. - Jing Wan; Zhilin Zhang 002; Bhaskar D. Rao; Shiaofen Fang; Jingwen Yan; Andrew J. Saykin; Li Shen 001 (IEEE Trans. Medical Imaging, 2014)

GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics. - Lei Du 001; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Heng Huang; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (BIH, 2015)

Integrated Visualization of Human Brain Connectome Data. - Huang Li; Shiaofen Fang; Joaquín Goñi; Joey A. Contreras; Yanhua Liang; Chengtao Cai; John D. West; Shannon L. Risacher; Yang Wang; Olaf Sporns; Andrew J. Saykin; Li Shen 001 (BIH, 2015)

Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut. - Hongchang Gao; Chengtao Cai; Jingwen Yan; Lin Yan 003; Joaquín Goñi Cortes; Yang Wang; Feiping Nie 001; John D. West; Andrew J. Saykin; Li Shen 001; Heng Huang (MICCAI (2), 2015)

Surface-based morphometric analysis of hippocampal subfields in mild cognitive impairment and Alzheimer's disease. - Shan Cong; Maher E. Rizkalla; Paul Salama; John D. West; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (MWSCAS, 2015)

The role of visualization and 3-D printing in biological data mining. - Talia Weiss; Amanda L. Zieselman; Douglas P. Hill; Solomon Gilbert Diamond; Li Shen 001; Andrew J. Saykin; Jason H. Moore (BioData Min., 2015)

Erratum to: Improving protein order-disorder classification using charge-hydropathy plots. - Fei Huang; Christopher J. Oldfield; Bin Xue; Wei-Lun Hsu; Jingwei Meng; Xiaowen Liu; Li Shen 001; Pedro Romero; Vladimir N. Uversky; A. Keith Dunker (BMC Bioinform., 2015)

Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics. - Lei Du 001; Tuo Zhang; Kefei Liu 001; Xiaohui Yao; Jingwen Yan; Shannon L. Risacher; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (BIBM, 2016)

New Probabilistic Multi-graph Decomposition Model to Identify Consistent Human Brain Network Modules. - Dijun Luo; Zhouyuan Huo; Yang Wang; Andrew J. Saykin; Li Shen 001; Heng Huang (ICDM, 2016)

A New Statistical Image Analysis Approach and Its Application to Hippocampal Morphometry. - Mark Inlow; Shan Cong; Shannon L. Risacher; John D. West; Maher E. Rizkalla; Paul Salama; Andrew J. Saykin; Li Shen 001 (MIAR, 2016)

Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration. - Shan Cong; Maher E. Rizkalla; Paul Salama; Shannon L. Risacher; John D. West; Yu-Chien Wu; Liana G. Apostolova; Eileen F. Tallman; Andrew J. Saykin; Li Shen 001 (MWSCAS, 2016)

Diagnosis-Guided Method for Identifying Multi-Modality Neuroimaging Biomarkers Associated with Genetic Risk Factors in Alzheimer's Disease. - Xiaoke Hao; Jingwen Yan; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Daoqiang Zhang; Li Shen 001 (PSB, 2016)

Multigraph Visualization for Feature Classification of Brain Network Data. - Jiachen Wang; Shiaofen Fang; Huang Li; Joaquín Goñi; Andrew J. Saykin; Li Shen 001 (EuroVA@EuroVis, 2016)

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: a study of ADNI cohorts. - Ailin Song; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Aaron K. Wong; Andrew J. Saykin; Li Shen 001; Casey S. Greene (BioData Min., 2016)

Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method. - Lei Du 001; Heng Huang; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Bioinform., 2016)

Structured sparse CCA for brain imaging genetics via graph OSCAR. - Lei Du 001; Heng Huang; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (BMC Syst. Biol., 2016)

Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer's Disease. - Xiaoke Hao; Xiaohui Yao; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Daoqiang Zhang; Li Shen 001 (Neuroinformatics, 2016)

BECA: A Software Tool for Integrated Visualization of Human Brain Data. - Huang Li; Shiaofen Fang; Bob Zigon; Olaf Sporns; Andrew J. Saykin; Joaquín Goñi; Li Shen 001 (BI, 2017)

Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules. - Xiaohui Yao; Jingwen Yan; Shannon L. Risacher; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (ICASSP, 2017)

Predicting High-Order Directional Drug-Drug Interaction Relations. - Xia Ning; Li Shen 001; Lang Li 001 (ICHI, 2017)

Pattern Discovery from Directional High-Order Drug-Drug Interaction Relations. - Xia Ning; Titus Schleyer; Li Shen 001; Lang Li 001 (ICHI, 2017)

Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach. - Lei Du 001; Tuo Zhang; Kefei Liu 001; Jingwen Yan; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Junwei Han 001; Lei Guo 002; Li Shen 001 (IPMI, 2017)

Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model. - Xiaoqian Wang 001; Kefei Liu 001; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Heng Huang (IPMI, 2017)

A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics. - Yuming Huang; Lei Du 001; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (GRAIL/MFCA/MICGen@MICCAI, 2017)

Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm. - Kefei Liu 001; Xiaohui Yao; Jingwen Yan; Danai Chasioti; Shannon L. Risacher; Kwangsik Nho; Andrew J. Saykin; Li Shen 001 (GRAIL/MFCA/MICGen@MICCAI, 2017)

Session Introduction. - Li Shen 001; Lee A. D. Cooper (PSB, 2017)

Identification of Discriminative Imaging Proteomics Associations in Alzheimer's Disease via a Novel Sparse Correlation Model>. - Jingwen Yan; Shannon L. Risacher; Kwangsik Nho; Andrew J. Saykin; Li Shen 001 (PSB, 2017)

Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model. - Xiaoqian Wang 001; Jingwen Yan; Xiaohui Yao; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Heng Huang (RECOMB, 2017)

Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis. - Xiaoke Hao; Chanxiu Li; Jingwen Yan; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Daoqiang Zhang (Bioinform., 2017)

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules. - Xiaohui Yao; Jingwen Yan; Kefei Liu 001; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Casey S. Greene; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Bioinform., 2017)

Brain explorer for connectomic analysis. - Huang Li; Shiaofen Fang; Joey A. Contreras; John D. West; Shannon L. Risacher; Yang Wang; Olaf Sporns; Andrew J. Saykin; Joaquín Goñi; Li Shen 001 (Brain Informatics, 2017)

Two-dimensional enrichment analysis for mining high-level imaging genetic associations. - Xiaohui Yao; Jingwen Yan; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Brain Informatics, 2017)

Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics. - Lei Du 001; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Junwei Han 001; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (BIBM, 2018)

A Unified Model for Robust Differential Expression Analysis of RNA-Seq Data. - Kefei Liu 001; Li Shen 001; Hui Jian (BIBM, 2018)

Interactive Machine Learning by Visualization: A Small Data Solution. - Huang Li; Shiaofen Fang; Snehasis Mukhopadhyay; Andrew J. Saykin; Li Shen 001 (IEEE BigData, 2018)

Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis. - Kai Liu 018; Hua Wang 007; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (ISBI, 2018)

Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning. - Lyujian Lu; Hua Wang 007; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (ISBI, 2018)

Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model. - Jingwen Yan; Kefei Liu 001; Huang Lv; Enrico Amico; Shannon L. Risacher; Yu-Chien Wu; Shiaofen Fang; Olaf Sporns; Andrew J. Saykin; Joaquín Goñi; Li Shen 001 (ISBI, 2018)

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease. - Lodewijk Brand; Hua Wang 007; Heng Huang; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001 (MICCAI (1), 2018)

Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms. - Ayagoz Mussabayeva; Alexey Kroshnin; Anvar Kurmukov; Yulia Denisova; Li Shen 001; Shan Cong; Lei Wang 032; Boris A. Gutman (ShapeMI@MICCAI, 2018)

Heritability Estimation of Reliable Connectomic Features. - Linhui Xie; Enrico Amico; Paul Salama; Yu-Chien Wu; Shiaofen Fang; Olaf Sporns; Andrew J. Saykin; Joaquín Goñi; Jingwen Yan; Li Shen 001 (CNI@MICCAI, 2018)

Session introduction. - Heng Huang; Li Shen 001; Paul M. Thompson; Kun Huang 001; Junzhou Huang; Lin Yang 002 (PSB, 2018)

Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data. - Jingwen Yan; Shannon L. Risacher; Li Shen 001; Andrew J. Saykin (Briefings Bioinform., 2018)

A novel SCCA approach via truncated ℓ1-norm and truncated group lasso for brain imaging genetics. - Lei Du 001; Kefei Liu 001; Tuo Zhang; Xiaohui Yao; Jingwen Yan; Shannon L. Risacher; Junwei Han 001; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (Bioinform., 2018)

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks. - Xiaoqian Wang 001; Hong Chen 004; Jingwen Yan; Kwangsik Nho; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Heng Huang (Bioinform., 2018)

Drug Recommendation toward Safe Polypharmacy. - Wen-Hao Chiang; Li Shen 001; Lang Li 001; Xia Ning (CoRR, 2018)

Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model. - Xiaoqian Wang 001; Jingwen Yan; Xiaohui Yao; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Heng Huang (J. Comput. Biol., 2018)

Pattern Discovery from High-Order Drug-Drug Interaction Relations. - Wen-Hao Chiang; Titus Schleyer; Li Shen 001; Lang Li 001; Xia Ning (J. Heal. Informatics Res., 2018)

GPU Accelerated Browser for Neuroimaging Genomics. - Bob Zigon; Huang Li; Xiaohui Yao; Shiaofen Fang; Mohammad Al Hasan; Jingwen Yan; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Neuroinformatics, 2018)

Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. - Bo Peng 009; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Xia Ning (BHI, 2019)

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis. - Xiaohui Yao; Shan Cong; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Jason H. Moore; Li Shen 001 (BHI, 2019)

Statistical Inference on the Number of Cycles in Brain Networks. - Moo K. Chung; Shih-Gu Huang; Andrey Gritsenko; Li Shen 001; Hyekyoung Lee (ISBI, 2019)

Diagnosis Status Guided Brain Imaging Genetics Via Integrated Regression And Sparse Canonical Correlation Analysis. - Lei Du 001; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (ISBI, 2019)

Rapid Acceleration of the Permutation Test via Transpositions. - Moo K. Chung; Linhui Xie; Shih-Gu Huang; Yixian Wang; Jingwen Yan; Li Shen 001 (CNI@MICCAI, 2019)

A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics. - Lei Du 001; Fang Liu; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Junwei Han 001; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (MICCAI (4), 2019)

Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models. - Ayagoz Mussabayeva; Maxim Pisov; Anvar Kurmukov; Alexey Kroshnin; Yulia Denisova; Li Shen 001; Shan Cong; Lei Wang 032; Boris Gutman (MBIA/MFCA@MICCAI, 2019)

Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank. - Bo Peng 009; Zhiyun Ren; Xiaohui Yao; Kefei Liu 001; Andrew J. Saykin; Li Shen 001; Xia Ning (MBIA/MFCA@MICCAI, 2019)

Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort. - Lei Du 001; Kefei Liu 001; Lei Zhu 011; Xiaohui Yao; Shannon L. Risacher; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (Bioinform., 2019)

Joint between-sample normalization and differential expression detection through ℓ 0-regularized regression. - Kefei Liu 001; Li Shen 001; Hui Jiang 002 (BMC Bioinform., 2019)

Identifying Candidate Genetic Associations with MRI-Derived AD-Related ROI via Tree-Guided Sparse Learning. - Xiaoke Hao; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Jintai Yu; Huifu Wang; Lan Tan; Li Shen 001; Daoqiang Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

A Unified Model for Joint Normalization and Differential Gene Expression Detection in RNA-Seq Data. - Kefei Liu 001; Jieping Ye; Yang Yang; Li Shen 001; Hui Jiang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Mining Directional Drug Interaction Effects on Myopathy Using the FAERS Database. - Danai Chasioti; Xiaohui Yao; Pengyue Zhang; Samuel Lerner; Sara K. Quinney; Xia Ning; Lang Li 001; Li Shen 001 (IEEE J. Biomed. Health Informatics, 2019)

Polygenic mediation analysis of Alzheimer's disease implicated intermediate amyloid imaging phenotypes. - Yingxuan Eng; Xiaohui Yao; Kefei Liu 001; Shannon L. Risacher; Andrew J. Saykin; Qi Long; Yize Zhao; Li Shen 001 (AMIA, 2020)

Estimating Hard-tissue Conditions from Dental Images via Machine Learning. - Jingxuan Bao; Mansu Kim; Qing Sun; Anderson T. Hara; Gerardo Maupome; Li Shen 001 (BIBE, 2020)

Deep Multiview Learning to Identify Population Structure with Multimodal Imaging. - Yixue Feng 001; Mansu Kim; Xiaohui Yao; Kefei Liu 001; Qi Long; Li Shen 001 (BIBE, 2020)

Deep Network-Based Feature Selection for Imaging Genetics: Application to Identifying Biomarkers for Parkinson's Disease. - Mansu Kim; Ji Hye Won; Jisu Hong; Junmo Kwon; Hyunjin Park; Li Shen 001 (ISBI, 2020)

Structural Connectivity Enriched Functional Brain Network Using Simplex Regression with GraphNet. - Mansu Kim; Jingxaun Bao; Kefei Liu 001; Bo-yong Park; Hyunjin Park; Li Shen 001 (MLMI@MICCAI, 2020)

Persistent Feature Analysis of Multimodal Brain Networks Using Generalized Fused Lasso for EMCI Identification. - Jin Li 012; Chenyuan Bian; Dandan Chen; Xianglian Meng; Haoran Luo; Hong Liang; Li Shen 001 (MICCAI (7), 2020)

Spatial Similarity-Aware Learning and Fused Deep Polynomial Network for Detection of Obsessive-Compulsive Disorder. - Peng Yang 011; Qiong Yang; Wei Zheng 009; Li Shen 001; Tianfu Wang 001; Ziwen Peng; Baiying Lei (MICCAI (7), 2020)

Predicting Longitudinal Outcomes of Alzheimer's Disease via a Tensor-Based Joint Classification andRegression Model. - Lodewijk Brand; Kai Nichols; Hua Wang 007; Heng Huang; Li Shen 001 (PSB, 2020)

Ideas for how informaticians can get involved with COVID-19 research. - Jason H. Moore; Ian Barnett; Mary Regina Boland; Yong Chen 016; George Demiris; Graciela Gonzalez-Hernandez; Daniel S. Herman; Blanca E. Himes; Rebecca A. Hubbard; Dokyoon Kim; Jeffrey S. Morris; Danielle L. Mowery; et al. (BioData Min., 2020)

Identifying diagnosis-specific genotype-phenotype associations via joint multitask sparse canonical correlation analysis and classification. - Lei Du 001; Fang Liu; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Junwei Han 001; Lei Guo 002; Andrew J. Saykin; Li Shen 001 (Bioinform., 2020)

Regional imaging genetic enrichment analysis. - Xiaohui Yao; Shan Cong; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Jason H. Moore; Li Shen 001 (Bioinform., 2020)

Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020. - Yan Guo; Li Shen 001; Xinghua Shi; Kai Wang 063; Yulin Dai; Zhongming Zhao (BMC Bioinform., 2020)

Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study. - Jin Li 012; Chenyuan Bian; Dandan Chen; Xianglian Meng; Haoran Luo; Hong Liang; Li Shen 001 (BMC Bioinform., 2020)

Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. - Bo Peng 009; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Xia Ning (CoRR, 2020)

Grouping effects of sparse CCA models in variable selection. - Kefei Liu 001; Qi Long; Li Shen 001 (CoRR, 2020)

Drug-drug interaction prediction based on co-medication patterns and graph matching. - Wen-Hao Chiang; Li Shen 001; Lang Li 001; Xia Ning (Int. J. Comput. Biol. Drug Des., 2020)

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes. - 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 001 (Int. J. Comput. Biol. Drug Des., 2020)

Enhanced Balanced Min Cut. - Xiaojun Chen 006; Weijun Hong; Feiping Nie 001; Joshua Zhexue Huang; Li Shen 001 (Int. J. Comput. Vis., 2020)

Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach. - Lei Du 001; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Junwei Han 001; Andrew J. Saykin; Lei Guo 002; Li Shen 001 (Medical Image Anal., 2020)

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease. - Xiaoke Hao; Yongjin Bao; Yingchun Guo; Ming Yu 006; Daoqiang Zhang; Shannon L. Risacher; Andrew J. Saykin; Xiaohui Yao; Li Shen 001 (Medical Image Anal., 2020)

Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data. - Bo Peng 009; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Xia Ning (BMC Medical Informatics Decis. Mak., 2020)

Informatics and machine learning methods for health applications. - Li Shen 001; Xinghua Shi; Zhongming Zhao; Kai Wang 063 (BMC Medical Informatics Decis. Mak., 2020)

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease. - Manhua Liu; Fan Li; Hao Yan; Kundong Wang; Yixin Ma; Li Shen 001; Mingqing Xu (NeuroImage, 2020)

Hierarchical Structured Sparse Learning for Schizophrenia Identification. - Mingliang Wang; Xiaoke Hao; Jiashuang Huang; Kangcheng Wang; Li Shen 001; Xijia Xu; Daoqiang Zhang; Mingxia Liu 001 (Neuroinformatics, 2020)

Brain Imaging Genomics: Integrated Analysis and Machine Learning. - Li Shen 001; Paul M. Thompson (Proc. IEEE, 2020)

Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction. - Lodewijk Brand; Kai Nichols; Hua Wang 007; Li Shen 001; Heng Huang (IEEE Trans. Medical Imaging, 2020)

Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method. - Lei Du 001; Fang Liu; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Junwei Han 001; Andrew J. Saykin; Li Shen 001 (IEEE Trans. Medical Imaging, 2020)

Mining and visualizing high-order directional drug interaction effects using the FAERS database. - Xiaohui Yao; Tiffany Tsang; Qing Sun; Sara K. Quinney; Pengyue Zhang; Xia Ning; Lang Li 001; Li Shen 001 (BMC Medical Informatics Decis. Mak., 2020)

Interactive Visualization of Deep Learning for 3D Brain Data Analysis. - Huang Li; Shiaofen Fang; Joaquín Goñi; Andrew J. Saykin; Li Shen 001 (ICCI*CC, 2021)

Interpretable temporal graph neural network for prognostic prediction of Alzheimer's disease using longitudinal neuroimaging data. - Mansu Kim; Jaesik Kim; Jeffrey Qu; Heng Huang; Qi Long; Kyung-Ah Sohn; Dokyoon Kim; Li Shen 001 (BIBM, 2021)

Brain imaging genetics: integrated analysis and machine learning. - Li Shen 001 (BIBM, 2021)

Topological Learning and Its Application to Multimodal Brain Network Integration. - Tananun Songdechakraiwut; Li Shen 001; Moo K. Chung (MICCAI (2), 2021)

A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits. - Yize Zhao; Xiwen Zhao; Mansu Kim; Jingxuan Bao; Li Shen 001 (MICCAI (5), 2021)

Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics. - Junhao Wen 002; Cynthia H. Y. Fu; Duygu Tosun; Yogasudha Veturi; Zhijian Yang; Ahmed Abdulkadir; Elizabeth Mamourian; Dhivya Srinivasan; Jingxuan Bao; Güray Erus; Haochang Shou; Mohamad Habes; et al. (CoRR, 2021)

A structural enriched functional network: An application to predict brain cognitive performance. - Mansu Kim; Jingxuan Bao; Kefei Liu 001; Bo-yong Park; Hyunjin Park; Jae Young Baik; Li Shen 001 (Medical Image Anal., 2021)

Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions. - Lyujian Lu; Saad Elbeleidy; Lauren Zoe Baker; Hua Wang 007; Li Shen 001; Heng Huang (IEEE Trans. Biomed. Eng., 2021)

Multi-Task Sparse Canonical Correlation Analysis with Application to Multi-Modal Brain Imaging Genetics. - Lei Du 001; Kefei Liu 001; Xiaohui Yao; Shannon L. Risacher; Junwei Han 001; Andrew J. Saykin; Lei Guo 002; Li Shen 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Identify Consistent Cross-Modality Imaging Genetic Patterns via Discriminant Sparse Canonical Correlation Analysis. - Meiling Wang 001; Wei Shao 005; Xiaoke Hao; Li Shen 001; Daoqiang Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Connectome transformer with anatomically inspired attention for Parkinson's diagnosis. - Diego Machado Reyes; Mansu Kim; Hanqing Chao; Li Shen 001; Pingkun Yan (BCB, 2022)

Genomics transformer for diagnosing Parkinson's disease. - Diego Machado Reyes; Mansu Kim; Hanqing Chao; Juergen Hahn; Li Shen 001; Pingkun Yan (BHI, 2022)

Mediation Analysis and Mixed-Effects Models for the Identification of Stage-specific Imaging Genetics Patterns in Alzheimer's Disease. - Daniele Pala; Brian Lee; Xia Ning; Dokyoon Kim; Li Shen 001 (BIBM, 2022)

Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. - Jiahang Sha; Jingxuan Bao; Kefei Liu 001; Shu Yang 009; Zixuan Wen; Yuhan Cui; Junhao Wen 002; Christos Davatzikos; Jason H. Moore; Andrew J. Saykin; Qi Long; Li Shen 001 (BIBM, 2022)

Using Optimal Transport to Improve Spherical Harmonic Quantification of Complex Biological Shapes. - Zexuan Wang; Wenxi Yang; Katharine Ryan; Sumita Garai; Benjamin M. Auerbach; Li Shen 001 (BIBM, 2022)

Consistency of Graph Theoretical Measurements of Alzheimer's Disease Fiber Density Connectomes Across Multiple Parcellation Scales. - Frederick H. Xu; Sumita Garai; Duy Duong-Tran; Andrew J. Saykin; Yize Zhao; Li Shen 001 (BIBM, 2022)

Tensor-Based Multi-Modal Multi-Target Regression for Alzheimer's Disease Prediction. - Jun Yu; Benjamin Zalatan; Yong Chen 016; Li Shen 001; Lifang He 001 (BIBM, 2022)

Interpretable Graph Convolutional Network Of Multi-Modality Brain Imaging For Alzheimer's Disease Diagnosis. - Houliang Zhou; Lifang He 001; Yu Zhang 009; Li Shen 001; Brian Chen (ISBI, 2022)

Sparse Interpretation of Graph Convolutional Networks for Multi-modal Diagnosis of Alzheimer's Disease. - Houliang Zhou; Yu Zhang 009; Brian Y. Chen; Li Shen 001; Lifang He 001 (MICCAI (8), 2022)

Large-Scale Simulation of Quantum Computational Chemistry on a New Sunway Supercomputer. - Honghui Shang; Li Shen 001; Yi Fan; Zhiqian Xu 005; Chu Guo; Jie Liu 069; Wenhao Zhou; Huan Ma; Rongfen Lin; Yuling Yang; Fang Li; Zhuoya Wang; et al. (SC, 2022)

Integrating multi-omics summary data using a Mendelian randomization framework. - Chong Jin; Brian Lee; Li Shen 001; Qi Long (Briefings Bioinform., 2022)

Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment. - Yixue Feng 001; Mansu Kim; Xiaohui Yao; Kefei Liu 001; Qi Long; Li Shen 001 (BMC Bioinform., 2022)

Identifying genes associated with brain volumetric differences through tissue specific transcriptomic inference from GWAS summary data. - Hung Mai; Jingxuan Bao; Paul M. Thompson; Dokyoon Kim; Li Shen 001 (BMC Bioinform., 2022)

Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis. - Jun Yu; Zhaoming Kong; Liang Zhan; Li Shen 001; Lifang He 001 (CoRR, 2022)

Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. - Mansu Kim; Eun Jeong Min; Kefei Liu 001; Jingwen Yan; Andrew J. Saykin; Jason H. Moore; Qi Long; Li Shen 001 (Medical Image Anal., 2022)

Diagnosis of obsessive-compulsive disorder via spatial similarity-aware learning and fused deep polynomial network. - Peng Yang 011; Cheng Zhao 003; Qiong Yang; Wei Zheng 009; Xiaohua Xiao; Li Shen 001; Tianfu Wang 001; Baiying Lei; Ziwen Peng (Medical Image Anal., 2022)

Multi-Group Tensor Canonical Correlation Analysis. - Zhuoping Zhou; Boning Tong; Davoud Ataee Tarzanagh; Bojian Hou; Andrew J. Saykin; Qi Long; Li Shen 001 (BCB, 2023)

Causal Effects of Environmental Exposures and Biological Traits on the Difference between Phenotypic and Chronological Ages. - Daniele Pala; Yuezhi Xie; Jia Xu; Yuqin Zhang; Li Shen 001 (BIBM, 2023)

Interpretable Graph Convolutional Network for Alzheimer's Disease Diagnosis using Multi-Modal Imaging Genetics. - Houliang Zhou; Yu Zhang 009; Lifang He 001; Li Shen 001; Brian Y. Chen (BIBM, 2023)

Integrating Multimodal Contrastive Learning and Cross-Modal Attention for Alzheimer's Disease Prediction in Brain Imaging Genetics. - Rong Zhou; Houliang Zhou; Li Shen 001; Brian Y. Chen; Yu Zhang 009; Lifang He 001 (BIBM, 2023)

Identifying Shared Neuroanatomic Architecture Between Cognitive Traits Through Multiscale Morphometric Correlation Analysis. - Zixuan Wen; Jingxuan Bao; Shu Yang 009; Shannon L. Risacher; Andrew J. Saykin; Paul M. Thompson; Christos Davatzikos; Heng Huang; Yize Zhao; Li Shen 001 (MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI, 2023)

Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer's Disease Using Multimodal Imaging Genetics. - Rong Zhou; Houliang Zhou; Brian Y. Chen; Li Shen 001; Yu Zhang 009; Lifang He 001 (MICCAI (2), 2023)

Shape analysis of amygdala atrophy using SPHARM-OT. - Zexuan Wang; Jiong Chen; Wenxi Yang; Sumita Garai; Frederick H. Xu; Junhao Wen 002; Christos Davatzikos; Li Shen 001 (Image Processing, 2023)

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. - Boning Tong; Zhuoping Zhou; Davoud Ataee Tarzanagh; Bojian Hou; Andrew J. Saykin; Jason H. Moore; Marylyn D. Ritchie; Li Shen 001 (MLMI@MICCAI (2), 2023)

Fair Canonical Correlation Analysis. - Zhuoping Zhou; Davoud Ataee Tarzanagh; Bojian Hou; Boning Tong; Jia Xu; Yanbo Feng; Qi Long; Li Shen 001 (NeurIPS, 2023)

Fairness-aware class imbalanced learning on multiple subgroups. - Davoud Ataee Tarzanagh; Bojian Hou; Boning Tong; Qi Long; Li Shen 001 (UAI, 2023)

Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering. - Zhijian Yang; Junhao Wen 002; Ahmed Abdulkadir; Yuhan Cui; Güray Erus; Elizabeth Mamourian; Randa Melhem; Dhivya Srinivasan; Sindhuja T. Govindarajan; Jiong Chen; Mohamad Habes; Colin L. Masters; et al. (CoRR, 2023)

Incomplete Multimodal Learning for Complex Brain Disorders Prediction. - Reza Shirkavand; Liang Zhan; Heng Huang; Li Shen 001; Paul M. Thompson (CoRR, 2023)

Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing. - Shunian Xiang; Patrick J. Lawrence; Bo Peng 009; Chienwei Chiang; Dokyoon Kim; Li Shen 001; Xia Ning (CoRR, 2023)

Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis. - Jingxuan Bao; Changgee Chang; Qiyiwen Zhang; Andrew J. Saykin; Li Shen 001; Qi Long (Briefings Bioinform., 2023)

Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer's disease. - Jingxuan Bao; Junhao Wen 002; Zixuan Wen; Shu Yang 009; Yuhan Cui; Zhijian Yang; Güray Erus; Andrew J. Saykin; Qi Long; Christos Davatzikos; Li Shen 001 (NeuroImage, 2023)

Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model. - Duy Minh Ho Nguyen; An Thai Le 001; Trung Quoc Nguyen; Nghiem Tuong Diep; Tai Nguyen 008; Duy Duong-Tran; Jan Peters 001; Li Shen 001; Mathias Niepert; Daniel Sonntag (ACML, 2024)

Integrative Analysis of Amyloid Imaging and Genetics Reveals Subtypes of Alzheimer Progression in Early Stage. - Bing He; Neel Sangani; Ruiming Wu; Pradeep Varathan; Alice Patania; Shannon L. Risacher; Kwangsik Nho; Liana G. Apostolova; Andrew J. Saykin; Li Shen 001; Jingwen Yan (AIME (2), 2024)

Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods. - Davoud Ataee Tarzanagh; Parvin Nazari; Bojian Hou; Li Shen 001; Laura Balzano (AISTATS, 2024)

Towards Instructing Disease-Drug Link Prediction with Social Determinants of Health. - Yashaswi Galhotra; Ying Ding 001; Li Shen 001; Huanmei Wu; Tianlong Chen 001; Kaixiong Zhou (BCB, 2024)

Causality-based Subject and Task Fingerprints using fMRI Time-series Data. - Dachuan Song; Li Shen 001; Duy Duong-Tran; Xuan Wang 013 (BCB, 2024)

Caudal and Thalamic Segregation in White Matter Brain Network Communities in Alzheimer's Disease Population. - Frederick H. Xu; Duy Duong-Tran; Yize Zhao; Li Shen 001 (BHI, 2024)

SEFD: Semantic-Enhanced Framework for Detecting LLM-Generated Text. - Weiqing He; Bojian Hou; Tianqi Shang; Davoud Ataee Tarzanagh; Qi Long; Li Shen 001 (IEEE Big Data, 2024)

DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature. - Dawei Li 008; Shu Yang 009; Zhen Tan 001; Jae Young Baik; Sukwon Yun; Joseph Lee; Aaron Chacko; Bojian Hou; Duy Duong-Tran; Ying Ding 001; Huan Liu 001; Li Shen 001; et al. (EMNLP (Findings), 2024)

Preserving Human Large-Scale Brain Connectivity Fingerprint Identifiability with Random Projections. - Duy Duong-Tran; Mark Magsino; Joaquín Goñi; Li Shen 001 (ISBI, 2024)

Mapping Alzheimer's Disease Pseudo-Progression With Multimodal Biomarker Trajectory Embeddings. - Lina Takemaru; Shu Yang 009; Ruiming Wu; Bing He; Christos Davtzikos; Jingwen Yan; Li Shen 001 (ISBI, 2024)

Multiscale Estimation of Morphometricity for Revealing Neuroanatomical Basis of Cognitive Traits. - Zixuan Wen; Jingxuan Bao; Shu Yang 009; Junhao Wen 002; Qipeng Zhan; Yuhan Cui; Güray Erus; Zhijian Yang; Paul M. Thompson; Yize Zhao; Christos Davatzikos; Li Shen 001 (ISBI, 2024)

Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification. - Sion An; Myeongkyun Kang; Soopil Kim; Philip Chikontwe; Li Shen 001; Sang Hyun Park 004 (MICCAI (11), 2024)

Volume-Optimal Persistence Homological Scaffolds of Hemodynamic Networks Covary with MEG Theta-Alpha Aperiodic Dynamics. - Nghi Nguyen; Tao Hou; Enrico Amico; Jingyi Zheng; Huajun Huang; Alan D. Kaplan; Giovanni Petri; Joaquín Goñi; Ralph Kaufmann; Yize Zhao; Duy Duong-Tran; Li Shen 001 (MICCAI (3), 2024)

Fairness-Aware Estimation of Graphical Models. - Zhuoping Zhou; Davoud Ataee Tarzanagh; Bojian Hou; Qi Long; Li Shen 001 (NeurIPS, 2024)

QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics. - Zexuan Wang; Qipeng Zhan; Shu Yang 009; Shizhuo Mu; Jiong Chen; Sumita Garai; Patryk Orzechowski; Joost B. Wagenaar; Li Shen 001 (Briefings Bioinform., 2024)

Deep learning-based approaches for multi-omics data integration and analysis. - Jenna l. Ballard; Zexuan Wang; Wenrui Li; Li Shen 001; Qi Long (BioData Min., 2024)

Multimodal Neurodegenerative Disease Subtyping Explained by ChatGPT. - Diego Machado Reyes; Hanqing Chao; Juergen Hahn; Li Shen 001; Pingkun Yan (CoRR, 2024)

Fine-Tuning Linear Layers Only Is a Simple yet Effective Way for Task Arithmetic. - Ruochen Jin; Bojian Hou; Jiancong Xiao; Weijie J. Su; Li Shen 001 (CoRR, 2024)

SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH). - Bernardo Consoli; Xizhi Wu; Song Wang 026; Xinyu Zhao; Yanshan Wang; Justin F. Rousseau; Tom Hartvigsen; Li Shen 001; Huanmei Wu; Yifan Peng 002; Qi Long; Tianlong Chen 001; et al. (CoRR, 2024)

Theorizing neuro-induced relationships between cognitive diversity, motivation, grit and academic performance in multidisciplinary engineering education context. - Duy Duong-Tran; Siqing Wei; Li Shen 001 (CoRR, 2024)

Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models. - Joseph Lee; Shu Yang 009; Jae Young Baik; Xiaoxi Liu; Zhen Tan 001; Dawei Li 008; Zixuan Wen; Bojian Hou; Duy Duong-Tran; Tianlong Chen 001; Li Shen 001 (CoRR, 2024)

Clustering Alzheimer's Disease Subtypes via Similarity Learning and Graph Diffusion. - Tianyi Wei; Shu Yang 009; Davoud Ataee Tarzanagh; Jingxuan Bao; Jia Xu; Patryk Orzechowski; Joost B. Wagenaar; Qi Long; Li Shen 001 (CoRR, 2024)

Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs. - Tianqi Shang; Shu Yang 009; Weiqing He; Tianhua Zhai; Dawei Li 008; Bojian Hou; Tianlong Chen 001; Jason H. Moore; Marylyn D. Ritchie; Li Shen 001 (CoRR, 2024)

Integrating Social Determinants of Health into Knowledge Graphs: Evaluating Prediction Bias and Fairness in Healthcare. - Tianqi Shang; Weiqing He; Tianlong Chen 001; Ying Ding 001; Huanmei Wu; Kaixiong Zhou; Li Shen 001 (CoRR, 2024)

Interpretable deep clustering survival machines for Alzheimer's disease subtype discovery. - Bojian Hou; Zixuan Wen; Jingxuan Bao; Richard Zhang; Boning Tong; Shu Yang 009; Junhao Wen 002; Yuhan Cui; Jason H. Moore; Andrew J. Saykin; Heng Huang; Paul M. Thompson; et al. (Medical Image Anal., 2024)

Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic. - Ruochen Jin; Bojian Hou; Jiancong Xiao; Weijie J. Su; Li Shen 001 (ICLR, 2025)

High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy. - Hanxiang Xu; Shizhuo Mu; Jingxuan Bao; Christos Davatzikos; Haochang Shou; Li Shen 001 (BioData Min., 2025)

Modeling the impact of socioeconomic disparity, biological markers and environmental exposures on phenotypic age using mediation analysis and structural equation models. - Daniele Pala; Yuezhi Xie; Jia Xu; Li Shen 001 (Int. J. Medical Informatics, 2025)

Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling. - Selena Wang; Yiting Wang; Frederick H. Xu; Li Shen 001; Yize Zhao (Medical Image Anal., 2025)

Multi-Modal Diagnosis of Alzheimer's Disease Using Interpretable Graph Convolutional Networks. - Houliang Zhou; Lifang He 001; Brian Y. Chen; Li Shen 001; Yu Zhang 009 (IEEE Trans. Medical Imaging, 2025)

MentalChat16K: A Benchmark Dataset for Conversational Mental Health Assistance. - Jia Xu; Tianyi Wei; Bojian Hou; Patryk Orzechowski; Shu Yang 009; Ruochen Jin; Rachael Paulbeck; Joost B. Wagenaar; George Demiris; Li Shen 001 (CoRR, 2025)

ICAFS: Inter-Client-Aware Feature Selection for Vertical Federated Learning. - Ruochen Jin; Boning Tong; Shu Yang 009; Bojian Hou; Li Shen 001 (CoRR, 2025)

Investigating LLMs in Clinical Triage: Promising Capabilities, Persistent Intersectional Biases. - Joseph Lee; Tianqi Shang; Jae Young Baik; Duy Duong-Tran; Shu Yang 009; Lingyao Li; Li Shen 001 (CoRR, 2025)

Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach. - Jiancong Xiao; Bojian Hou; Zhanliang Wang; Ruochen Jin; Qi Long; Weijie J. Su; Li Shen 001 (CoRR, 2025)

Reconstructing Brain Causal Dynamics for Subject and Task Fingerprints using fMRI Time-series Data. - Dachuan Song; Li Shen 001; Duy Duong-Tran; Xuan Wang 013 (CoRR, 2025)

Fair CCA for Fair Representation Learning: An ADNI Study. - Bojian Hou; Zhanliang Wang; Zhuoping Zhou; Boning Tong; Zexuan Wang; Jingxuan Bao; Duy Duong-Tran; Qi Long; Li Shen 001 (CoRR, 2025)

Enabling Few-Shot Alzheimer's Disease Diagnosis on Tabular Biomarker Data with LLMs. - Sophie Kearney; Shu Yang 009; Zixuan Wen; Bojian Hou; Duy Duong-Tran; Tianlong Chen 001; Jason H. Moore; Marylyn D. Ritchie; Li Shen 001 (CoRR, 2025)

Subject-adaptive meta-learning for personalized BCI: A fusion of resting-state EEG signal and task-specific information. - Sion An; Myeongkyun Kang; Soopil Kim; Philip Chikontwe; Li Shen 001; Sang Hyun Park 004 (Inf. Fusion, 2026)