Research graph
References from Multi-modal intermediate integrative methods in neuropsychiatric disorders: A review. Local targets link to admitted publications; unresolved targets remain external evidence.
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Brain imaging genomics: integrated analysis and machine learning
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Plasma Amyloid as Prescreener for the Earliest Alzheimer Pathological Changes
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Cerebrospinal fluid and plasma biomarker trajectories with increasing amyloid deposition in Alzheimer's disease
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Unresolved reference
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Multi-omics approaches to disease
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In search of multimodal neuroimaging biomarkers of cognitive deficits in schizophrenia
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Unresolved reference
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Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer’s Disease via Fusion of Clinical, Imaging and Omic Features
10.1038/s41598-017-03925-0 · 2017 · External reference
A strategy for multimodal data integration: application to biomarkers identification in spinocerebellar ataxia
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Joint-Connectivity-Based Sparse Canonical Correlation Analysis of Imaging Genetics for Detecting Biomarkers of Parkinson's Disease
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Three-way (N-way) fusion of brain imaging data based on mCCA+jICA and its application to discriminating schizophrenia
10.1016/j.neuroimage.2012.10.051 · 2013 · External reference
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Hyper-graph based sparse canonical correlation analysis for the diagnosis of Alzheimer's disease from multi-dimensional genomic data
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2020 · External reference
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Unresolved reference
2017 · External reference
Integration of Imaging (epi)Genomics Data for the Study of Schizophrenia Using Group Sparse Joint Nonnegative Matrix Factorization
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Brain-behavior participant similarity networks among youth and emerging adults with schizophrenia spectrum, autism spectrum, or bipolar disorder and matched controls
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Multimodal phenotypic axes of Parkinson's disease
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Alzheimer's disease neuroimaging, prediction and classification of alzheimer's disease based on combined features from apolipoprotein-e genotype, cerebrospinal Fluid, MR, and FDG-PET imaging biomarkers
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Multimodal MR Images-Based Diagnosis of Early Adolescent Attention-Deficit/Hyperactivity Disorder Using Multiple Kernel Learning
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Improving Alzheimer's Disease Classification by Combining Multiple Measures
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Alzheimers disease neuroimaging, predictive markers for AD in a multi-modality framework: an analysis of MCI progression in the ADNI population
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Multiple kernel learning in the primal for multimodal Alzheimer's disease classification
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Structured sparsity regularized multiple kernel learning for Alzheimer's disease diagnosis
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Multi-view subspace clustering analysis for aggregating multiple heterogeneous omics data
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A hybrid computational approach for efficient Alzheimer's disease classification based on heterogeneous data
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Alzheimer's disease neuroimaging, heterogeneous multimodal biomarkers analysis for Alzheimer's disease via Bayesian network
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Alzheimer's disease neuroimaging, bayesian latent time joint mixed effect models for multicohort longitudinal data
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Bayesian latent time joint mixed-effects model of progression in the Alzheimer's Disease Neuroimaging Initiative
10.1016/j.dadm.2018.07.008 · 2018 · External reference
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A Robust Deep Model for Improved Classification of AD/MCI Patients
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Nonlinear feature transformation and deep fusion for Alzheimer's Disease staging analysis
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Alzheimer's disease neuroimaging, latent feature representation with stacked auto-encoder for AD/MCI diagnosis
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A multi-modal fusion of features method based on deep belief networks to diagnosis schizophrenia disease
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Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning
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2021 · External reference
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Heterogeneous Multi-Layered Network Model for Omics Data Integration and Analysis
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