VNN-based brain age gap analysis finds distinct anatomical patterns in Alzheimer's, frontotemporal dementia, and atypical Parkinsonian disorders, but not in Parkinson's disease.
A single layer of VNN is formed by concate- nating a coVariance filter with a pointwise non-linear activa- tion function σ(·) (e.g., ReLU, tanh) that satisfies σ(u) = [σ(u1),
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Explainable Brain Age Gap Prediction in Neurodegenerative Conditions using coVariance Neural Networks
VNN-based brain age gap analysis finds distinct anatomical patterns in Alzheimer's, frontotemporal dementia, and atypical Parkinsonian disorders, but not in Parkinson's disease.