Shannon L. Risacher

Orcid: 0000-0002-3304-7943

According to our database1, Shannon L. Risacher authored at least 78 papers between 2010 and 2024.

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Bibliography

2024
Fused multi-modal similarity network as prior in guiding brain imaging genetic association.
Frontiers Big Data, 2024

Learning the Irreversible Progression Trajectory of Alzheimer's Disease.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Integrative Analysis of Amyloid Imaging and Genetics Reveals Subtypes of Alzheimer Progression in Early Stage.
Proceedings of the Artificial Intelligence in Medicine - 22nd International Conference, 2024

2023
Identifying Shared Neuroanatomic Architecture Between Cognitive Traits Through Multiscale Morphometric Correlation Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

2021
Multi-Task Sparse Canonical Correlation Analysis with Application to Multi-Modal Brain Imaging Genetics.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Tau-related white-matter alterations along spatially selective pathways.
NeuroImage, 2021

Deep Fusion of Brain Structure-Function in Mild Cognitive Impairment.
Medical Image Anal., 2021

Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer's disease.
Briefings Bioinform., 2021

2020
Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method.
IEEE Trans. Medical Imaging, 2020

Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data.
BMC Medical Informatics Decis. Mak., 2020

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease.
Medical Image Anal., 2020

Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach.
Medical Image Anal., 2020

Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data.
CoRR, 2020

Deep learning detection of informative features in tau PET for Alzheimer's disease classification.
BMC Bioinform., 2020

Regional imaging genetic enrichment analysis.
Bioinform., 2020

Identifying diagnosis-specific genotype-phenotype associations via joint multitask sparse canonical correlation analysis and classification.
Bioinform., 2020

Polygenic mediation analysis of Alzheimer's disease implicated intermediate amyloid imaging phenotypes.
Proceedings of the AMIA 2020, 2020

2019
Identifying Candidate Genetic Associations with MRI-Derived AD-Related ROI via Tree-Guided Sparse Learning.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort.
Bioinform., 2019

A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Diagnosis Status Guided Brain Imaging Genetics Via Integrated Regression And Sparse Canonical Correlation Analysis.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

2018
Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model.
J. Comput. Biol., 2018

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks.
Bioinform., 2018

A novel SCCA approach via truncated ℓ1-norm and truncated group lasso for brain imaging genetics.
Bioinform., 2018

Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data.
Briefings Bioinform., 2018

Codon bias among synonymous rare variants is associated with Alzheimer's disease imaging biomarker.
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018

Towards Subject and Diagnostic Identifiability in the Alzheimer's Disease Spectrum Based on Functional Connectomes.
Proceedings of the Graphs in Biomedical Image Analysis - and - Integrating Medical Imaging and Non-Imaging Modalities, 2018

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017
Two-dimensional enrichment analysis for mining high-level imaging genetic associations.
Brain Informatics, 2017

Brain explorer for connectomic analysis.
Brain Informatics, 2017

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules.
Bioinform., 2017

Identification of associations between genotypes and longitudinal phenotypes via temporally-constrained group sparse canonical correlation analysis.
Bioinform., 2017

Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model.
Proceedings of the Research in Computational Molecular Biology, 2017

Identification of Discriminative Imaging Proteomics Associations in Alzheimer's Disease via a Novel Sparse Correlation Model>.
Proceedings of the Biocomputing 2017: Proceedings of the Pacific Symposium, 2017

Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm.
Proceedings of the Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017

A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics.
Proceedings of the Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017

Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model.
Proceedings of the Information Processing in Medical Imaging, 2017

Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach.
Proceedings of the Information Processing in Medical Imaging, 2017

Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer's Disease.
Neuroinformatics, 2016

Structured sparse CCA for brain imaging genetics via graph OSCAR.
BMC Syst. Biol., 2016

Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method.
Bioinform., 2016

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: a study of ADNI cohorts.
BioData Min., 2016

Diagnosis-Guided Method for Identifying Multi-Modality Neuroimaging Biomarkers Associated with Genetic Risk Factors in Alzheimer's Disease.
Proceedings of the Biocomputing 2016: Proceedings of the Pacific Symposium, 2016

Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration.
Proceedings of the IEEE 59th International Midwest Symposium on Circuits and Systems, 2016

A New Statistical Image Analysis Approach and Its Application to Hippocampal Morphometry.
Proceedings of the Medical Imaging and Augmented Reality - 7th International Conference, 2016

Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015
Surface-based morphometric analysis of hippocampal subfields in mild cognitive impairment and Alzheimer's disease.
Proceedings of the IEEE 58th International Midwest Symposium on Circuits and Systems, 2015

Integrated Visualization of Human Brain Connectome Data.
Proceedings of the Brain Informatics and Health - 8th International Conference, 2015

GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics.
Proceedings of the Brain Informatics and Health - 8th International Conference, 2015

2014
Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm.
Bioinform., 2014

Building a surface atlas of hippocampal subfields from MRI scans using FreeSurfer, FIRST and SPHARM.
Proceedings of the IEEE 57th International Midwest Symposium on Circuits and Systems, 2014

A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013
Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures.
Proceedings of the Multimodal Brain Image Analysis - Third International Workshop, 2013

PARP1 Gene Variation and Microglial Activity on [11C]PBR28 PET in Older Adults at Risk for Alzheimer's Disease.
Proceedings of the Multimodal Brain Image Analysis - Third International Workshop, 2013

A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI).
Proceedings of the Multimodal Brain Image Analysis - Third International Workshop, 2013

Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions.
Proceedings of the Information Processing in Medical Imaging, 2013

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].
NeuroImage, 2012

A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort.
NeuroImage, 2012

From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs.
Bioinform., 2012

Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning.
Bioinform., 2012

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort.
Bioinform., 2012

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning.
Proceedings of the Multimodal Brain Image Analysis - Second International Workshop, 2012

Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

Hippocampal Surface Mapping of Genetic Risk Factors in AD via Sparse Learning Models.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net.
Proceedings of the Multimodal Brain Image Analysis, First International Workshop, 2011

Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance.
Proceedings of the IEEE International Conference on Computer Vision, 2011

2010
Age-related neuroinflammation in non-demented elderly adults: Preliminary findings with the TSPO ligand [11C]PBR28.
NeuroImage, 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.
NeuroImage, 2010

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010


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