Machine Learning in Clinical Neuroimaging

.- Machine learning.
.- Parkinson's Disease Detection from Resting State EEG using Multi-Head Graph  Structure Learning with Gradient Weighted Graph Attention Explanations.
.- ProxiMO: Proximal Multi-Operator Networks for Quantitative Susceptibility Mapping.
.- Brain-Cognition Fingerprinting via Graph-GCCA with Contrastive Learning.
.- HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks.
.- SpaRG - Sparsely Reconstructed Graphs for Generalizable fMRI Analysis.
.- A Lightweight 3D Conditional Diffusion Model for Self-Explainable Brain Age  Prediction in Adults and Children.
.- SOE: SO(3)-Equivariant 3D MRI Encoding.
.- Towards a foundation model for cortical folding.
.- Clinical Applications.
.- A Lesion-aware Edge-based Graph Neural Network for Predicting Language Ability in  Patients with Post-stroke Aphasia.
.- DISARM: Disentangled Scanner-free Image Generation via Unsupervised Image2Image 
Translation.
.- Segmenting Small Stroke Lesions with Novel Labeling Strategies.
.- A Progressive Single-Modality to Multi-Modality Classification Framework for  Alzheimer’s Disease Sub-type Diagnosis.
.- Surface-based parcellation and vertex-wise analysis of ultra high-resolution ex vivo 7  tesla MRI in Alzheimer's disease and related dementias.
.- Self-Supervised Pre-training Tasks for an fMRI Time-series Transformer in Autism  Detection.
.- Is Your Style Transfer Doing Anything Useful? An Investigation Into Hippocampus  Segmentation and the Role of Preprocessing.
.- GAMing the Brain: Investigating the Cross-modal Relationships between Functional  Connectivity and Structural Features using Generalized Additive Models.