Olga Trofimova

This study benchmarks attention-based interpretability methods for Vision Transformers in retinal fundus imaging, finding gradient-weighted attention rollout provides the most faithful and biologically relevant attributions.

This study identifies sex-specific genetic and environmental contributions to retinal vascular traits through GWAS and interaction analyses, highlighting the need for sex-aware approaches in precision medicine.

The paper develops a deep learning model to measure carotid lumen diameter from ultrasounds and performs GWAS, finding cLD has higher heritability and stronger associations with cardiovascular risk factors than cIMT.

The paper analyzes retinal vascular phenotypes from fundus images and their genetic and disease associations using UK Biobank data, finding novel links between vascular features and health outcomes.