Emma J. Gleave

The paper uses polygenic scores from GWAS to identify spatial genetic effects on brain structure across multiple scales in MRI data.

This paper identifies widespread gray and white matter volume differences in autism using a large voxel-based morphometry analysis of 3,051 participants.

The paper maps the focal and generalized effects of common genetic variants on human brain structure using polygenic scores and MRI data.

This study compares deep learning methods to predict cognitive decline using brain MRI and clinical data over two years, showing the value of integrating image and tabular data.

This study evaluates deep learning models that predict multiple dementia-related neuropathologies using MRI, clinical, and genetic data, showing the potential of multimodal AI for non-invasive profiling.

This study compares explainable AI models for Alzheimer's disease classification using MRI scans, evaluating interpretability methods and generalization across different populations.