Andrew J. Saykin

发表

Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease

Shannon L. Risacher, Andrew J. Saykin, Bhaskar D. Rao, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Diagnosis Status Guided Brain Imaging Genetics Via Integrated Regression And Sparse Canonical Correlation Analysis

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2013, MBIA.

Identification of Discriminative Imaging Proteomics Associations in Alzheimer's Disease via a Novel Sparse Correlation Model>

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, PSB.

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Classification and Mining of Brain Image Data Using Adaptive Recursive Partitioning Methods: Application to Alzheimer Disease and Brain Activation Patterns

Fillia Makedon, Andrew J. Saykin, Zoran Obradovic, 2003 .

Cognitive biomarker prioritization in Alzheimer’s Disease using brain morphometric data

Shannon L. Risacher, Andrew J. Saykin, Xiaohui Yao, 2020, BMC Medical Informatics and Decision Making.

Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2017, IPMI.

Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, IPMI.

A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics

Lei Guo, Shannon L. Risacher, Andrew J. Saykin, 2019, MICCAI.

A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI)

Michael Weiner, Shannon L. Risacher, Andrew J. Saykin, 2013, MBIA.

New Probabilistic Multi-graph Decomposition Model to Identify Consistent Human Brain Network Modules

Yang Wang, Andrew J. Saykin, Heng Huang, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services

Andrew J. Saykin, Daniel Bullock, Olaf Sporns, 2018, Scientific Data.

Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model

Joaquín Goñi, Enrico Amico, Shannon L. Risacher, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Pattern Visualization of Human Connectome Data

Yang Wang, Andrew J. Saykin, Hongyang Chao, 2012, EuroVis.

Optimizing Differential Identifiability Improves Connectome Predictive Modeling of Cognitive Deficits in Alzheimer\'s Disease

Diana O. Svaldi, Enrico Amico, Shannon L. Risacher, 2019 .

A spatio-temporal multi-modal data management and analysis environment for tracking MS lesions

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, 15th International Conference on Scientific and Statistical Database Management, 2003..

Bootstrapped Sparse Canonical Correlation Analysis

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2018 .

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]

Shannon L. Risacher, Andrew J. Saykin, Vince D. Calhoun, 2012, NeuroImage.

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes

Andrew J. Saykin, Jingwen Yan, Olaf Sporns, 2020, Int. J. Comput. Biol. Drug Des..

Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, 2011 International Conference on Computer Vision.

Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning

Andrew J. Saykin, Bhaskar D. Rao, Zhilin Zhang, 2014, IEEE Transactions on Medical Imaging.

Patient Classification of fMRI Activation Maps

Fillia Makedon, Andrew J. Saykin, Vasileios Megalooikonomou, 2003, MICCAI.

Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, 2016, Neuroinformatics.

Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays

Andrew J. Saykin, Olaf Sporns, Franco Pestilli, 2017, NIPS.

Morphometric Analysis of Brain Structures for Improved Discrimination

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, MICCAI.

From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease

Shannon L. Risacher, Andrew J. Saykin, Hua Wang, 2018, MICCAI.

Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer’s Pathophysiology

Norbert Schuff, Michael W. Weiner, Andrew J. Saykin, 2020, Scientific Reports.

Exploring Interestingness in a Computational Evolution System for the Genome-Wide Genetic Analysis of Alzheimer's Disease

Andrew J. Saykin, Jason H. Moore, Li Shen, 2013, GPTP.

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

Michael Weiner, Shannon L. Risacher, John D. West, 2010, NeuroImage.

Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis

Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, 2017, Bioinform..

Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, GRAIL/MFCA/MICGen@MICCAI.

MULTIMODAL-CNN: IMPROVED ACCURACY OF MRI-BASED CLASSIFICATION OF ALZHEIMER’S DISEASE BY INCORPORATING CLINICAL DATA IN DEEP LEARNING

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2018, Alzheimer's & Dementia.

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2010, NeuroImage.

Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data pdf

Shannon L. Risacher, Andrew J. Saykin, Li Shen, 2020, ArXiv.

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

Yuan Qi, Shannon L. Risacher, Andrew J. Saykin, 2010, MICCAI.

Interactive Machine Learning by Visualization: A Small Data Solution

Andrew J. Saykin, Huang Li, Shiaofen Fang, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Human Connectome Module Pattern Detection Using a New Multi-graph MinMax Cut Model

Yang Wang, Andrew J. Saykin, Feiping Nie, 2014, MICCAI.

Brain explorer for connectomic analysis

Yang Wang, Joaquín Goñi, Shannon L. Risacher, 2017, Brain Informatics.

TROI - A training and research system for tracing regions of interest in brain images

Andrew J. Saykin, Li Shen, Ling Cheng, 2001, NeuroImage.

Building a surface atlas of hippocampal subfields from MRI scans using FreeSurfer, FIRST and SPHARM

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2014, 2014 IEEE 57th International Midwest Symposium on Circuits and Systems (MWSCAS).

Tensor encoding and decomposition of brain connectomes with application to tractography evaluation

Andrew J. Saykin, Olaf Sporns, Franco Pestilli, 2017, NIPS 2017.

A New Statistical Image Analysis Approach and Its Application to Hippocampal Morphometry

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2016, MIAR.

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks

Hong Chen, Shannon L. Risacher, Andrew J. Saykin, 2018, Bioinform..

Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

PATHWAY LEVEL CODON BIAS AMONG SYNONYMOUS RARE VARIANTS IS ASSOCIATED WITH ALZHEIMER’S DISEASE IMAGING BIOMARKER

Shannon L. Risacher, Andrew J. Saykin, Do Kyoon Kim, 2018, Alzheimer's & Dementia.

A Novel Surface Registration Algorithm With Biomedical Modeling Applications

Fillia Makedon, Andrew J. Saykin, Heng Huang, 2007, IEEE Transactions on Information Technology in Biomedicine.

Deep learning detection of informative features in tau PET for Alzheimer’s disease classification

Shannon L. Risacher, Andrew J. Saykin, Kwangsik Nho, 2020, BMC Bioinform..

Disruption of gene co-expression network along the progression of Alzheimer's disease

Andrew J. Saykin, Jingwen Yan, Paul Salama, 2019, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

Longitudinal measurement and hierarchical classification framework for the prediction of Alzheimer’s disease

Andrew J. Saykin, Arthur W. Toga, Qianjin Feng, 2017, Scientific Reports.

Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification

Norbert Schuff, Michael W. Weiner, Andrew J. Saykin, 2019, Scientific Reports.

Morphometric Analysis of Hippocampal Shape in Mild Cognitive Impairment: An Imaging Genetics Study

Andrew J. Saykin, Moo K. Chung, Heng Huang, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data

Shannon L. Risacher, Andrew J. Saykin, Bo Peng, 2019, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

GPU Accelerated Browser for Neuroimaging Genomics

Andrew J. Saykin, Huang Li, Jingwen Yan, 2018, Neuroinformatics.

MetaDL: A Digital Library of Metadata for Sensitive or Complex Research Data

Fillia Makedon, Andrew J. Saykin, Li Shen, 2002, ECDL.

Regional reproducibility of pulsed arterial spin labeling perfusion imaging at 3T

Chen Lin, Yang Wang, Andrew J. Saykin, 2011, NeuroImage.

Heritability Estimation of Reliable Connectomic Features

Joaquín Goñi, Enrico Amico, Andrew J. Saykin, 2018, CNI@MICCAI.

A novel SCCA approach via truncated ℓ1-norm and truncated group lasso for brain imaging genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2017, Bioinform..

Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut

Yang Wang, Lin Yan, Joaquín Goñi, 2015, MICCAI.

Extraction of Discriminative Functional MRI Activation Patterns and an Application to Alzheimer's Disease

Fillia Makedon, Andrew J. Saykin, Zoran Obradovic, 2004, MICCAI.

EVALUATION METRICS FOR USER-CENTERED RANKING OF CONTENT IN METADLs

Fillia Makedon, Andrew J. Saykin, Li Shen, 2004 .

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2014, Bioinform..

A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis

Andrew J. Saykin, Feiping Nie, Jingwen Yan, 2013, MICCAI.

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer’s disease: a study of ADNI cohorts

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, BioData Mining.

Comparison of multi-sample variant calling methods for whole genome sequencing

Michael W. Weiner, Robert C. Green, John D. West, 2014, 2014 8th International Conference on Systems Biology (ISB).

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: Optimization and reproducibility

Andrew J. Saykin, Yang Wang, Olaf Sporns, 2013, NeuroImage.

Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning

Shannon L. Risacher, Andrew J. Saykin, Hua Wang, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

BECA: A Software Tool for Integrated Visualization of Human Brain Data

Joaquín Goñi, Andrew J. Saykin, Huang Li, 2017, BI.

Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2016, Bioinform..

Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2013, IPMI.

Shannon L. Risacher, Andrew J. Saykin, Qiuting Wen, 2020, NeuroImage.

Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data

Andrew J. Saykin, Taeho Jo, Kwangsik Nho, 2019, Front. Aging Neurosci..

Multigraph Visualization for Feature Classification of Brain Network Data

Joaquín Goñi, Andrew J. Saykin, Huang Li, 2016, EuroVA@EuroVis.

A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2014, MICCAI.

A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2017, GRAIL/MFCA/MICGen@MICCAI.

An interactive user interface system for Alzheimer's intervention

Fillia Makedon, Andrew J. Saykin, Heng Huang, 2010, PETRA '10.

Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank

Andrew J. Saykin, Bo Peng, Kefei Liu, 2019, MBIA/MFCA@MICCAI.

Computational genetics analysis of grey matter density in Alzheimer’s disease

Andrew J. Saykin, Ting Hu, Jason H. Moore, 2014, BioData Mining.

Efficient Registration of 3D SPHARM Surfaces

Fillia Makedon, Andrew J. Saykin, Heng Huang, 2007, Fourth Canadian Conference on Computer and Robot Vision (CRV '07).

Fourier method for large-scale surface modeling and registration

Andrew J. Saykin, Li Shen, Sungeun Kim, 2009, Comput. Graph..

Hippocampal shape analysis: surface-based representation and classification

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, SPIE Medical Imaging.

Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, MICCAI.

A ROBUST, SIMPLIFIED BRAAK-TYPE CLASSIFICATION SCHEME FOR FLORTAUCIPIR F-18 TAU PET IMAGES

Shannon L. Risacher, Andrew J. Saykin, Adam J. Schwarz, 2017, Alzheimer's & Dementia.

Identifying significant gene‐environment interactions using a combination of screening testing and hierarchical false discovery rate control

Andrew J. Saykin, Jason H. Moore, Li Shen, 2016, Genetic epidemiology.

The role of visualization and 3-D printing in biological data mining

Andrew J. Saykin, Jason H. Moore, Li Shen, 2015, BioData Mining.

Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net

Yuan Qi, Michael Weiner, Shannon L. Risacher, 2011, MBIA.

GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2015, BIH.

Characteristics and variability of structural networks derived from diffusion tensor imaging

Yang Wang, Andrew J. Saykin, Jinhua Sheng, 2012, NeuroImage.

Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2016, 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS).

Two-Dimensional Enrichment Analysis for Mining High-Level Imaging Genetic Associations

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, BIH.

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, NIPS.

Optimization of seed density in DTI tractography for structural networks

Andrew J. Saykin, Yang Wang, Olaf Sporns, 2012, Journal of Neuroscience Methods.

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2012, MBIA.

Voxelwise gene-wide association study (vGeneWAS): Multivariate gene-based association testing in 731 elderly subjects

Michael Weiner, Andrew J. Saykin, Paul M. Thompson, 2011, NeuroImage.

Data synthesis and tool development for exploring imaging genomic patterns

John D. West, Andrew J. Saykin, Li Shen, 2009, 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Briefings Bioinform..

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2019, 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

Accelerating Sparse Canonical Correlation Analysis for Large Brain Imaging Genetics Data

Andrew J. Saykin, Lei Du, Jingwen Yan, 2014, XSEDE '14.

Stimulus tracking in functional magnetic resonance imaging (fMRI)

Fillia Makedon, Andrew J. Saykin, Sterling C. Johnson, 1998, MULTIMEDIA '98.

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants

Andrew J. Saykin, Ye Wang, Xiao Qin, 2020, bioRxiv.

Hippocampal Surface Mapping of Genetic Risk Factors in AD via Sparse Learning Models

Michael Weiner, Shannon L. Risacher, Andrew J. Saykin, 2011, MICCAI.

Quantifying Evolving Processes in Multimodal 3D Medical Images

Fillia Makedon, Andrew J. Saykin, Yuhang Wang, 2003, MICCAI.

Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning

Andrew J. Saykin, Jingwen Yan, Jason H. Moore, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis

Shannon L. Risacher, Andrew J. Saykin, Kai Liu, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

PARP1 Gene Variation and Microglial Activity on [11C]PBR28 PET in Older Adults at Risk for Alzheimer's Disease

Shannon L. Risacher, John D. West, Andrew J. Saykin, 2013, MBIA.

Integrated Visualization of Human Brain Connectome Data

Yang Wang, Joaquín Goñi, Shannon L. Risacher, 2015, BIH.

Voxelwise genome-wide association study (vGWAS)

Andrew J. Saykin, Paul M. Thompson, Arthur W. Toga, 2010, NeuroImage.

Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A large scale multivariate parallel ICA method reveals novel imaging–genetic relationships for Alzheimer's disease in the ADNI cohort

Shannon L. Risacher, Andrew J. Saykin, Vince D. Calhoun, 2012, NeuroImage.

Diagnosis-Guided Method for Identifying Multi-Modality Neuroimaging Biomarkers Associated with Genetic Risk Factors in Alzheimer's Disease

Daoqiang Zhang, Shannon L. Risacher, Andrew J. Saykin, 2016, PSB.

Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer’s disease

Andrew J. Saykin, Marylyn D. Ritchie, Do Kyoon Kim, 2017, BMC Medical Informatics and Decision Making.

Structured sparse CCA for brain imaging genetics via graph OSCAR

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2016, BMC Systems Biology.

A Novel Joint Brain Network Analysis Using Longitudinal Alzheimer’s Disease Data

Norbert Schuff, Michael W. Weiner, Andrew J. Saykin, 2019, Scientific Reports.

Tissue‐specific network‐based genome wide study of amygdala imaging phenotypes to identify functional interaction modules

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Bioinform..

Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics

Shannon L. Risacher, Andrew J. Saykin, Lei Du, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A surface-based approach for classification of 3D neuroanatomic structures

Fillia Makedon, Andrew J. Saykin, Li Shen, 2004, Intell. Data Anal..

Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, RECOMB.

Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method

Shannon L. Risacher, Andrew J. Saykin, Xiaohui Yao, 2020, IEEE Transactions on Medical Imaging.

A system framework for the integration and analysis of multi-modal spatiotemporal data streams: a case study in MS lesion analysis

Fillia Makedon, Andrew J. Saykin, Li Shen, 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..

Two-dimensional enrichment analysis for mining high-level imaging genetic associations

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2016, Brain Informatics.

Genetic Clustering on the Hippocampal Surface for Genome-Wide Association Studies

Andrew J. Saykin, Paul M. Thompson, Li Shen, 2013, MICCAI.

Shape-based discriminative analysis of combined bilateral hippocampi using multiple object alignment

Fillia Makedon, Andrew J. Saykin, Li Shen, 2004, SPIE Medical Imaging.

Data synthesis and method evaluation for brain imaging genetics

Andrew J. Saykin, Jingwen Yan, Jason H. Moore, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's disease

Michael Weiner, Andrew J. Saykin, Paul M. Thompson, 2010, NeuroImage.

Shannon L. Risacher, Andrew J. Saykin, Liana G. Apostolova, 2020, NeuroImage.

Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics pdf

Andrew J. Saykin, Christos Davatzikos, Marylyn D. Ritchie, 2021, ArXiv.

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants

Andrew J. Saykin, Ye Wang, Yuchao Jiang, 2021, Briefings Bioinform..

Progress in Polygenic Composite Scores in Alzheimer's and Other Complex Diseases.

Andrew J. Saykin, Jingwen Yan, Kwangsik Nho, 2019, Trends in genetics : TIG.

GENETIC FINDINGS USING ADNI MULTIMODAL QUANTITATIVE PHENOTYPES: A 2016 UPDATE

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2017, Alzheimer's & Dementia.

Hippocampal Atrophy as a Quantitative Trait in a Genome-Wide Association Study Identifying Novel Susceptibility Genes for Alzheimer's Disease

Andrew J. Saykin, Jessica A. Turner, Steven G. Potkin, 2009, PloS one.

Metabolic network failures in Alzheimer's disease: A biochemical road map

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2017, Alzheimer's & Dementia.

Altered Brain Connectivity in Early Postmenopausal Women with Subjective Cognitive Impairment

Andrew J. Saykin, Paul A. Newhouse, Neil Woodward, 2016, Front. Neurosci..

The fornix and mammillary bodies in older adults with Alzheimer's disease, mild cognitive impairment, and cognitive complaints: A volumetric MRI study

Andrew J. Saykin, Laura A. Flashman, Robert B. Santulli, 2006, Psychiatry Research: Neuroimaging.

The Interleukin 3 Gene (IL3) Contributes to Human Brain Volume Variation by Regulating Proliferation and Survival of Neural Progenitors

Andrew J. Saykin, Li Shen, Guillén Fernández, 2012, PloS one.

Genetic Interactions Explain Variance in Cingulate Amyloid Burden: An AV-45 PET Genome-Wide Association and Interaction Study in the ADNI Cohort

Andrew J. Saykin, Jingwen Yan, Li Shen, 2015, BioMed research international.

Acute effect of anterior temporal lobectomy on musical processing

Andrew J. Saykin, Ruben C. Gur, Michael R. Sperling, 1991, Neuropsychologia.

Implementation of subjective cognitive decline criteria in research studies

Andrew J. Saykin, Stefan Klöppel, Michael Wagner, 2017, Alzheimer's & Dementia.

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2016, Nature Communications.

Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer’s disease

Shannon L. Risacher, Andrew J. Saykin, Li Shen, 2012, Brain Imaging and Behavior.

Common genetic variants in the CLDN2 and PRSS1-PRSS2 loci alter risk for alcohol-related and sporadic pancreatitis

Robert C. Green, Andrew J. Saykin, Liana G. Apostolova, 2012, Nature Genetics.

The genetic architecture of the human cerebral cortex

Anders M. Dale, Robert C. Green, Shannon L. Risacher, 2020, Science.

Functional neuroanatomical correlates of episodic memory impairment in early phase psychosis

Andrew J. Saykin, Brenna C. McDonald, Alexander J. Radnovich, 2015, Brain Imaging and Behavior.

Exceptionally low likelihood of Alzheimer’s dementia in APOE2 homozygotes from a 5,000-person neuropathological study

Robert C. Green, Andrew J. Saykin, Liana G. Apostolova, 2020, Nature Communications.

Cortical surface biomarkers for predicting cognitive outcomes using group l 2,1 norm

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, Neurobiology of Aging.

The pattern of atrophy in familial Alzheimer disease

Andrew J. Saykin, Paul M. Thompson, Sébastien Ourselin, 2013, Neurology.

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

Norbert Schuff, Robert C. Green, Andrew J. Saykin, 2017 .

Author Correction: Multimodal hippocampal subfield grading for Alzheimer’s disease classification

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2020, Scientific Reports.

Neuropsychological Assessment of Neuropsychiatric Disorders

Andrew J. Saykin, Ruben C. Gur, R. Gur, 1988 .

Mapre2 as a novel Alzheimer's disease target gene from gwas of CSF amyloid beta 1-42, tau and hyperphosphorylated tau in the ADNI cohort

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2015, Alzheimer's & Dementia.

Olfactory identification in subjective cognitive decline and mild cognitive impairment: Association with tau but not amyloid positron emission tomography

Shannon L. Risacher, Andrew J. Saykin, Liana G. Apostolova, 2017, Alzheimer's & dementia.

Volumetric, cortical thickness and grey matter density changes on MRI over 12 months: Relationship to conversion status in the ADNI cohort

Shannon L. Risacher, Andrew J. Saykin, Li Shen, 2009, Alzheimer's & Dementia.

Alzheimer disease brain atrophy subtypes are associated with cognition and rate of decline

Shannon L. Risacher, Andrew J. Saykin, Adam J. Schwarz, 2017, Neurology.

Gene-based GWAS and biological pathway analysis of the resilience of executive functioning

Andrew J. Saykin, Kwangsik Nho, Nilüfer Ertekin-Taner, 2013, Brain Imaging and Behavior.

A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly

Michael W. Weiner, Andrew J. Saykin, Paul M. Thompson, 2010, Proceedings of the National Academy of Sciences.

Cognitive complaints in older adults at risk for Alzheimer's disease are associated with altered resting-state networks

Joaquín Goñi, Enrico Amico, Shannon L. Risacher, 2016, Alzheimer's & dementia.

DNA METHYLATION DYNAMICS IN ALZHEIMER’S DISEASE DIAGNOSIS AND PROGRESSION

Andrew J. Saykin, Kwangsik Nho, Karol Estrada, 2017, Alzheimer's & Dementia.

Mining Outcome-relevant Brain Imaging Genetic Associations via Three-way Sparse Canonical Correlation Analysis in Alzheimer’s Disease

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2017, Scientific Reports.

APOE effect on Alzheimer’s biomarkers in older adults with significant memory concern

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2015 .

The Relationship between fMRI Activation and Cerebral Atrophy: Comparison of Normal Aging and Alzheimer Disease

Andrew J. Saykin, Sterling C. Johnson, Thomas W. McAllister, 2000, NeuroImage.

Regionally specific atrophy of the corpus callosum in AD, MCI and cognitive complaints

Andrew J. Saykin, Laura A. Flashman, Robert B. Santulli, 2006, Neurobiology of Aging.

Alterations in brain structure and function in breast cancer survivors: effect of post-chemotherapy interval and relation to oxidative DNA damage

Andrew J. Saykin, Brenna C. McDonald, Susan K. Conroy, 2012, Breast Cancer Research and Treatment.

The genetic architecture of the human cerebral cortex

Anders M. Dale, Robert C. Green, Shannon L. Risacher, 2020, Science.

Externalizing personality traits, empathy, and gray matter volume in healthy young drinkers

Mario Dzemidzic, Andrew J. Saykin, Brandon G. Oberlin, 2016, Psychiatry Research: Neuroimaging.

Genome-wide analysis reveals novel genes in fl uencing temporal lobe structure with relevance to neurodegeneration in Alzheimer ' s disease

Michael W. Weiner, Andrew J. Saykin, Paul M. Thompson, 2010 .

Genome-wide association study of the rate of cognitive decline in Alzheimer's disease

Robert C. Green, Andrew J. Saykin, David A. Bennett, 2014, Alzheimer's & Dementia.

Hippocampal Volume and Shape Analysis in an Older Adult Population

Andrew J. Saykin, Laura A. Flashman, Heather A. Wishart, 2007, The Clinical neuropsychologist.

Candidate mechanisms for chemotherapy-induced cognitive changes

Andrew J. Saykin, Tim A. Ahles, A. Saykin, 2007, Nature Reviews Cancer.

White matter alterations in early-stage Alzheimer's disease: A tract-specific study

Shannon L. Risacher, Andrew J. Saykin, Liana G. Apostolova, 2019, Alzheimer's & dementia.

Resting state network modularity along the prodromal late onset Alzheimer's disease continuum

Joaquín Goñi, Shannon L. Risacher, Mario Dzemidzic, 2017, Alzheimer's & Dementia.

Genetic findings using ADNI multimodal quantitative phenotypes: A 2014 update

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2015, Alzheimer's & Dementia.

Genome-wide pathway analysis of memory impairment in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2012, Brain Imaging and Behavior.

Neural organization of material-specific memory functions in temporal lobe epilepsy patients as assessed by the intracarotid amobarbital test.

Andrew J. Saykin, Gayle K. Deutsch, Michael R. Sperling, 1995 .

Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults

Andrew J. Saykin, A. Saykin, P. Trzepacz, 2015, BMC Geriatrics.

Visual exploration of genetic association with voxel-based imaging phenotypes in an MCI/AD study

Andrew J. Saykin, Li Shen, Sungeun Kim, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach

Andrew J. Saykin, Steve Harenberg, Nagiza F. Samatova, 2017 .

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2016, Scientific Reports.

The Alzheimer’s Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans

Michael W. Weiner, Andrew J. Saykin, Robert A. Dean, 2015, Alzheimer's & Dementia.

“behavioral imaging”—III. Interexpert agreement and reliability of weightings

Andrew J. Saykin, Ruben C. Gur, Raquel E. Gur, 1990 .

Amyloid pathway-based candidate gene analysis of [11C]PiB-PET in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2011, Brain Imaging and Behavior.

“behavioral imaging”: II. Application of the quantitative algorithm to hypothesistesting in a population ofhemiparkinsonian patients

Andrew J. Saykin, Ruben C. Gur, Raquel E. Gur, 1988 .

Diagnostic Value of Subjective Memory Complaints Assessed with a Single Item in Dominantly Inherited Alzheimer's Disease: Results of the DIAN Study

Andrew J. Saykin, Christoph Laske, Adrian Danek, 2015, BioMed research international.

Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects

Michael W. Weiner, Andrew J. Saykin, Paul M. Thompson, 2012, Brain Imaging and Behavior.

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Anders M. Dale, Robert C. Green, Shannon L. Risacher, 2018, bioRxiv.

A Longitudinal Imaging Genetics Study of Neuroanatomical Asymmetry in Alzheimer’s Disease

Andrew J. Saykin, Christian Wachinger, Martin Reuter, 2018, Biological Psychiatry.

Targeted neurogenesis pathway-based gene analysis identifies ADORA2A associated with hippocampal volume in mild cognitive impairment and Alzheimer's disease

Michael W. Weiner, Shannon L. Risacher, Andrew J. Saykin, 2017, Neurobiology of Aging.

APOE ε4 and the risk for Alzheimer disease and cognitive decline in African Americans and Yoruba

Andrew J. Saykin, Kathleen A. Lane, Christopher M. Callahan, 2014, International Psychogeriatrics.

Large-scale genomics unveil polygenic architecture of human cortical surface area

Norbert Schuff, Anders M. Dale, Robert C. Green, 2015, Nature Communications.

Increased brain activation during working memory in cognitively intact adults with the APOE ε4 allele

Andrew J. Saykin, Thomas W. McAllister, Laura A. Flashman, 2006 .

P2-077: Comparison of manual and automated determination of hippocampal volumes in MCI and older adults with cognitive complaints

Andrew J. Saykin, Li Shen, Laura A. Flashman, 2008, Alzheimer's & Dementia.

Functional microRNAs in Alzheimer’s disease and cancer: differential regulation of common mechanisms and pathways

Andrew J. Saykin, Tatiana Foroud, A. Saykin, 2013, Front. Gene..

Impact of the Alzheimer's Disease Neuroimaging Initiative, 2004 to 2014

Michael W. Weiner, Robert C. Green, Andrew J. Saykin, 2015, Alzheimer's & Dementia.

“Behavioral imaging”―a procedure for analysis and display of neuropsychological test scores: I. construction of algorithm and initial clinical evaluation

Andrew J. Saykin, Ruben C. Gur, Raquel E. Gur, 1988 .

Cavum septum pellucidum in schizophrenia: Clinical and neuropsychological correlates

Andrew J. Saykin, Thomas W. McAllister, Laura A. Flashman, 2007, Psychiatry Research: Neuroimaging.

Nomenclature and research case definitions for neurologic manifestations of human immunodeficiency virus‐type 1 (HIV‐1) infection

Andrew J. Saykin, Norman Sartorius, James T. Becker, 1991, Neurology.

Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer’s disease

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2017, BMC Medical Genomics.

The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism

Shannon L. Risacher, Andrew J. Saykin, Liana G. Apostolova, 2016, Alzheimer's & dementia.

Differential Working Memory Load Effects after Mild Traumatic Brain Injury

Andrew J. Saykin, Thomas W. McAllister, Laura A. Flashman, 2001, NeuroImage.

Frontolimbic atrophy is associated with agitation and aggression in mild cognitive impairment and Alzheimer's disease

Andrew J. Saykin, Adam J. Schwarz, Peng Yu, 2013, Alzheimer's & Dementia.

Spatial comparison of fMRI activation maps for data mining

Fillia Makedon, Andrew J. Saykin, James Ford, 2001, NeuroImage.

Frontal gray matter reduction after breast cancer chemotherapy and association with executive symptoms: A replication and extension study

Andrew J. Saykin, Brenna C. McDonald, Susan K. Conroy, 2013, Brain, Behavior, and Immunity.

Regional brain atrophy in cognitively intact adults with a single APOE ε4 allele

Andrew J. Saykin, Thomas W. McAllister, Gregory J. Tsongalis, 2006, Neurology.

Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer disease: a longitudinal study

Andrew J. Saykin, Paul M. Thompson, Clifford R. Jack, 2018, The Lancet Neurology.

Hippocampus as a Predictor of Cognitive Performance : Comparative Evaluation of Analytical Methods and Morphometric Measures

Shannon L. Risacher, Andrew J. Saykin, Zhilin Zhang, 2012 .

430 Hippocampal volume reduction in schizophrenia as assessed by magnetic resonance imaging: A meta-analytic study

Andrew J. Saykin, Michael D. Nelson, Laura A. Flashman, 1997, Schizophrenia Research.

FOURIER METHODS FOR 3D SURFACE MODELING AND ANALYSIS

Andrew J. Saykin, Li Shen, John D. West, 2011 .

Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, Front. Genet..

Gray matter reduction associated with systemic chemotherapy for breast cancer: a prospective MRI study

Andrew J. Saykin, Brenna C. McDonald, Susan K. Conroy, 2010, Breast Cancer Research and Treatment.

Cholinergic Enhancement of Brain Activation in Mild Cognitive Impairment during Episodic Memory Encoding

Shannon L. Risacher, Andrew J. Saykin, Laura A. Flashman, 2013, Front. Psychiatry.

AbstractPoster presentation: Imaging posterIC-P1-054: Comparison of manual and automated determination of hippocampal volumes in MCI and older adults with cognitive complaints

Andrew J. Saykin, Li Shen, Laura A. Flashman, 2008 .

Subjective rating of working memory is associated with frontal lobe volume in schizophrenia

Andrew J. Saykin, Laura A. Flashman, Robert M. Roth, 2010, Schizophrenia Research.

Alterations in brain structure related to breast cancer and its treatment: chemotherapy and other considerations

Andrew J. Saykin, Brenna C. McDonald, A. Saykin, 2013, Brain Imaging and Behavior.

Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

Michael W. Weiner, Anders M. Dale, Robert C. Green, 2017, bioRxiv.

Apathy and the processing of novelty in schizophrenia

Andrew J. Saykin, Thomas W. McAllister, Laura A. Flashman, 2008, Schizophrenia Research.

Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics

Norbert Schuff, Michael W. Weiner, Robert C. Green, 2019, Scientific Reports.

Comparison of vertical and horizontal saccade measures and their relation to gray matter changes in premanifest and manifest Huntington disease

Mario Dzemidzic, Andrew J. Saykin, David A. Kareken, 2012, Journal of Neurology.

Andrew J. Saykin, Carl-Fredrik Westin, Ron Kikinis, 2008, Schizophrenia Research.

A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease

Andrew J. Saykin, Michael Wagner, Carole Dufouil, 2014, Alzheimer's & Dementia.

APOE and BCHE as modulators of cerebral amyloid deposition: a florbetapir PET genome-wide association study

Michael W. Weiner, Robert C. Green, Shannon L. Risacher, 2013, Molecular Psychiatry.

Lack of relationship between psychological denial and unawareness of illness in schizophrenia-spectrum disorders

Andrew J. Saykin, Laura A. Flashman, Robert M. Roth, 2009, Psychiatry Research.

Cognitive function in breast cancer patients prior to adjuvant treatment

Andrew J. Saykin, Peter A. Kaufman, Brenna C. McDonald, 2008, Breast Cancer Research and Treatment.

The Structural and Functional Connectome and Prediction of Risk for Cognitive Impairment in Older Adults

Joaquín Goñi, Shannon L. Risacher, Andrew J. Saykin, 2015, Current Behavioral Neuroscience Reports.

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Michael W. Weiner, Robert C. Green, Andrew J. Saykin, 2015, Alzheimer's & Dementia.

Topographic staging of tau positron emission tomography images

Shannon L. Risacher, Andrew J. Saykin, Adam J. Schwarz, 2018, Alzheimer's & dementia.