Andrew J. Saykin

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 77

Top Venues

Publications

Bing He, Neel Sangani, Ruiming Wu, Pradeep Varathan, Alice Patania, Shannon L. Risacher, Kwangsik Nho, Liana G. Apostolova, Andrew J. Saykin, Li Shen, Jingwen Yan
Integrative Analysis of Amyloid Imaging and Genetics Reveals Subtypes of Alzheimer Progression in Early Stage. AIME (2) (2024)
Bing He, Linhui Xie, Pradeep Varathan, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan
Fused multi-modal similarity network as prior in guiding brain imaging genetic association. Frontiers Big Data 6 (2024)
Yipei Wang, Bing He, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, Xiaoqian Wang
Learning the irreversible progression trajectory of Alzheimer's disease. CoRR (2024)
Bojian Hou, Zixuan Wen, Jingxuan Bao, Richard Zhang, Boning Tong, Shu Yang, Junhao Wen, Yuhan Cui, Jason H. Moore, Andrew J. Saykin, Heng Huang, Paul M. Thompson, Marylyn D. Ritchie, Christos Davatzikos, Li Shen
Interpretable deep clustering survival machines for Alzheimer's disease subtype discovery. Medical Image Anal. 97 (2024)
Boning Tong, Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Andrew J. Saykin, Jason H. Moore, Marylyn D. Ritchie, Li Shen
Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. MLMI@MICCAI (2) (2023)
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)
Jingxuan Bao, Junhao Wen, Zixuan Wen, Shu Yang, Yuhan Cui, Zhijian Yang, Güray Erus, Andrew J. Saykin, Qi Long, Christos Davatzikos, Li Shen
Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer's disease. NeuroImage 280 (2023)
Zhuoping Zhou, Boning Tong, Davoud Ataee Tarzanagh, Bojian Hou, Andrew J. Saykin, Qi Long, Li Shen
Multi-Group Tensor Canonical Correlation Analysis. BCB (2023)
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)
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)
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 (2022)
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)
Taeho Jo, Kwangsik Nho, Paula Bice, Andrew J. Saykin
Deep learning-based identification of genetic variants: application to Alzheimer's disease classification. Briefings Bioinform. 23 (2) (2022)
Linhui Xie, Bing He, Pradeep Varathan, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Paul Salama, Jingwen Yan
Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer's disease. Briefings Bioinform. 22 (6) (2021)
Ye Wang, Yuchao Jiang, Bing Yao, Kun Huang, Yunlong Liu, Yue Wang, Xiao Qin, Andrew J. Saykin, Li Chen
WEVar: a novel statistical learning framework for predicting noncoding regulatory variants. Briefings Bioinform. 22 (6) (2021)
Huang Li, Shiaofen Fang, Joaquín Goñi, Andrew J. Saykin, Li Shen
Interactive Visualization of Deep Learning for 3D Brain Data Analysis. ICCI*CC (2021)
Ye Wang, Tathagata Bhattacharya, Yuchao Jiang, Xiao Qin, Yue Wang, Yunlong Liu, Andrew J. Saykin, Li Chen
A novel deep learning method for predictive modeling of microbiome data. Briefings Bioinform. 22 (3) (2021)
Qiuting Wen, Shannon L. Risacher, Linhui Xie, Junjie Li, Jaroslaw Harezlak, Martin R. Farlow, Frederick W. Unverzagt, Sujuan Gao, Liana G. Apostolova, Andrew J. Saykin, Yu-Chien Wu
Tau-related white-matter alterations along spatially selective pathways. NeuroImage 226 (2021)
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 (2021)
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) (2021)
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) (2020)
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) (2020)
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) (2020)
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) (2020)
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)
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)
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) (2020)
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 (2020)
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 (2020)
Taeho Jo, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin
Deep learning detection of informative features in tau PET for Alzheimer's disease classification. BMC Bioinform. (21) (2020)
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) (2019)
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)
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)
Yurika Upadhyaya, Linhui Xie, Paul Salama, Kwangsik Nho, Andrew J. Saykin, Jingwen Yan
Disruption of gene co-expression network along the progression of Alzheimer's disease. BHI (2019)
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)
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) (2019)
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)
Taeho Jo, Kwangsik Nho, Andrew J. Saykin
Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data. CoRR (2019)
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)
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)
Jason E. Miller, Manu K. Shivakumar, Shannon L. Risacher, Andrew J. Saykin, SeungGeun Lee, Kwangsik Nho, Dokyoon Kim
Codon bias among synonymous rare variants is associated with Alzheimer's disease imaging biomarker. PSB (2018)
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) (2018)
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) (2018)
Diana O. Svaldi, Joaquín Goñi, Apoorva Bharthur Sanjay, Enrico Amico, Shannon L. Risacher, John D. West, Mario Dzemidzic, Andrew J. Saykin, Liana G. Apostolova
Towards Subject and Diagnostic Identifiability in the Alzheimer's Disease Spectrum Based on Functional Connectomes. GRAIL/Beyond-MIC@MICCAI (2018)
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)
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)
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) (2018)
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)
Huang Li, Shiaofen Fang, Snehasis Mukhopadhyay, Andrew J. Saykin, Li Shen
Interactive Machine Learning by Visualization: A Small Data Solution. IEEE BigData (2018)
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) (2018)
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)
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) (2018)
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)
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) (2017)
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)
Cesar F. Caiafa, Olaf Sporns, Andrew J. Saykin, Franco Pestilli
Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays. NIPS (2017)
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)
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)
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) (2017)
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) (2017)
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)
Jingwen Yan, Shannon L. Risacher, Kwangsik Nho, Andrew J. Saykin, Li Shen
Identification of Discriminative Imaging Proteomics Associations in Alzheimer's Disease via a Novel Sparse Correlation Model>. PSB (2017)
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)
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) (2017)
Dokyoon Kim, Anna Okula Basile, Lisa Bang, Emrin Horgusluoglu, SeungGeun Lee, Marylyn D. Ritchie, Andrew J. Saykin, Kwangsik Nho
Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer's disease. BMC Medical Informatics Decis. Mak. 17 (S-1) (2017)
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)
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)
Ailin Song, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Aaron K. Wong, Andrew J. Saykin, Li Shen, Casey S. Greene
Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: a study of ADNI cohorts. BioData Min. 9 (2016)
Jiachen Wang, Shiaofen Fang, Huang Li, Joaquín Goñi, Andrew J. Saykin, Li Shen
Multigraph Visualization for Feature Classification of Brain Network Data. EuroVA@EuroVis (2016)
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
Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration. MWSCAS (2016)
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) (2016)
Xiaoke Hao, Jingwen Yan, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Daoqiang Zhang, Li Shen
Diagnosis-Guided Method for Identifying Multi-Modality Neuroimaging Biomarkers Associated with Genetic Risk Factors in Alzheimer's Disease. PSB (2016)
Lei Du, Tuo Zhang, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen
Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics. BIBM (2016)
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) (2016)
Dijun Luo, Zhouyuan Huo, Yang Wang, Andrew J. Saykin, Li Shen, Heng Huang
New Probabilistic Multi-graph Decomposition Model to Identify Consistent Human Brain Network Modules. ICDM (2016)
Mark Inlow, Shan Cong, Shannon L. Risacher, John D. West, Maher E. Rizkalla, Paul Salama, Andrew J. Saykin, Li Shen
A New Statistical Image Analysis Approach and Its Application to Hippocampal Morphometry. MIAR (2016)
Xiaoke Hao, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Daoqiang Zhang, Li Shen
Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer's Disease. Neuroinformatics 14 (4) (2016)
Talia Weiss, Amanda L. Zieselman, Douglas P. Hill, Solomon Gilbert Diamond, Li Shen, Andrew J. Saykin, Jason H. Moore
The role of visualization and 3-D printing in biological data mining. BioData Min. 8 (2015)
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. BIH (2015)
Hongchang Gao, Chengtao Cai, Jingwen Yan, Lin Yan, Joaquín Goñi Cortes, Yang Wang, Feiping Nie, John D. West, Andrew J. Saykin, Li Shen, Heng Huang
Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut. MICCAI (2) (2015)
Shan Cong, Maher E. Rizkalla, Paul Salama, John D. West, Shannon L. Risacher, Andrew J. Saykin, Li Shen
Surface-based morphometric analysis of hippocampal subfields in mild cognitive impairment and Alzheimer's disease. MWSCAS (2015)
Yi Su, Tyler M. Blazey, Abraham Z. Snyder, Marcus E. Raichle, Daniel S. Marcus, Beau M. Ances, Randall J. Bateman, Nigel J. Cairns, Patricia Aldea, Lisa Cash, Jon J. Christensen, Karl Friedrichsen, Russ C. Hornbeck, Angela M. Farrar, Christopher J. Owen, Richard Mayeux, Adam M. Brickman, William E. Klunk, Julie C. Price, Paul M. Thompson, Bernardino Ghetti, Andrew J. Saykin, Reisa A. Sperling, Keith A. Johnson, Peter R. Schofield, Virginia Buckles, John C. Morris, Tammie L. S. Benzinger
Partial volume correction in quantitative amyloid imaging. NeuroImage 107 (2015)
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)
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
Integrated Visualization of Human Brain Connectome Data. BIH (2015)
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)
Jingwen Yan, Heng Huang, Sungeun Kim, Jason H. Moore, Andrew J. Saykin, Li Shen
Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning. ISBI (2014)
Jing Wan, Zhilin Zhang, Bhaskar D. Rao, Shiaofen Fang, Jingwen Yan, Andrew J. Saykin, Li Shen
Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning. IEEE Trans. Medical Imaging 33 (7) (2014)
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) (2014)
Shan Cong, Maher E. Rizkalla, Eliza Y. Du, John D. West, Shannon L. Risacher, Andrew J. Saykin, Li Shen
Building a surface atlas of hippocampal subfields from MRI scans using FreeSurfer, FIRST and SPHARM. MWSCAS (2014)
Jingwen Yan, Hui Zhang, Lei Du, Eric A. Wernert, Andrew J. Saykin, Li Shen
Accelerating Sparse Canonical Correlation Analysis for Large Brain Imaging Genetics Data. XSEDE (2014)
De Wang, Yang Wang, Feiping Nie, Jingwen Yan, Tom Weidong Cai, Andrew J. Saykin, Li Shen, Heng Huang
Human Connectome Module Pattern Detection Using a New Multi-graph MinMax Cut Model. MICCAI (3) (2014)
Jinhua Sheng, Sungeun Kim, Jingwen Yan, Jason H. Moore, Andrew J. Saykin, Li Shen
Data synthesis and method evaluation for brain imaging genetics. ISBI (2014)
Amanda L. Zieselman, Jonathan M. Fisher, Ting Hu, Peter C. Andrews, Casey S. Greene, Li Shen, Andrew J. Saykin, Jason H. Moore
Computational genetics analysis of grey matter density in Alzheimer's disease. BioData Min. 7 (2014)
Joaquín Goñi, Olaf Sporns, Hu Cheng, Maite Aznárez-Sanado, Yang Wang, Santiago Josa, Gonzalo Arrondo, Vincent P. Mathews, Tom A. Hummer, William G. Kronenberger, Andrea Avena-Koenigsberger, Andrew J. Saykin, María A. Pastor
Robust estimation of fractal measures for characterizing the structural complexity of the human brain: Optimization and reproducibility. NeuroImage 83 (2013)
Derrek P. Hibar, Sarah E. Medland, Jason L. Stein, Sungeun Kim, Li Shen, Andrew J. Saykin, Greig I. de Zubicaray, Katie McMahon, Grant W. Montgomery, Nicholas G. Martin, Margaret J. Wright, Srdjan Djurovic, Ingrid Agartz, Ole A. Andreassen, Paul M. Thompson
Genetic Clustering on the Hippocampal Surface for Genome-Wide Association Studies. MICCAI (2) (2013)
Dokyoon Kim, Sungeun Kim, Shannon L. Risacher, Li Shen, Marylyn D. Ritchie, Michael W. Weiner, Andrew J. Saykin, Kwangsik Nho
A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI). MBIA (2013)
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)
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)
Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Mark Inlow, Shanker Swaminathan, Karmen K. Yoder, Li Shen, John D. West, Brenna C. McDonald, Eileen F. Tallman, Gary D. Hutchins, James W. Fletcher, Martin R. Farlow, Bernardino Ghetti, Andrew J. Saykin
PARP1 Gene Variation and Microglial Activity on [11C]PBR28 PET in Older Adults at Risk for Alzheimer's Disease. MBIA (2013)
Heng Huang, Jingwen Yan, Feiping Nie, Jin Huang, Weidong Cai, Andrew J. Saykin, Li Shen
A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis. MICCAI (2) (2013)

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Publication Activity (10 Years)

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Andrew J. Saykin