ArticleFrontiers in neuroscience2015
Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition.
Article in Frontiers in neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease.Neuroinformatics · 2021Pooled it
- Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.PloS one · 2016Trial
- Synergistic effects of multicomponent exercise and rTMS on sarcopenia and mild cognitive impairment in older people: a protocol for a randomized controlled trial.BMC geriatrics · 2025Article
- Brain Network Classification for Accurate Detection of Alzheimer's Disease via Manifold Harmonic Discriminant Analysis.IEEE transactions on neural networks and learning systems · 2024Article
- Distributed Harmonization: Federated Clustered Batch Effect Adjustment and Generalization.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2024Article
- Disrupted excitation-inhibition balance in cognitively normal individuals at risk of Alzheimer's disease.bioRxiv : the preprint server for biology · 2023Article
- BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks.IEEE transactions on medical imaging · 2023Article
- Communicability Characterization of Structural DWI Subcortical Networks in Alzheimer's Disease.Entropy (Basel, Switzerland) · 2019Article
- Effects of Brain Parcellation on the Characterization of Topological Deterioration in Alzheimer's Disease.Frontiers in aging neuroscience · 2019Article
- Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.Nature communications · 2018Article
- Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework.NeuroImage. Clinical · 2018Article
- The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation1.Journal of Alzheimer's disease : JAD · 2018Article
- Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2017Review
- The Abnormality of Topological Asymmetry between Hemispheric Brain White Matter Networks in Alzheimer's Disease and Mild Cognitive Impairment.Frontiers in aging neuroscience · 2017Article
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8 authors.
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Abstract
Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying different stages of Alzheimer's disease.
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