Saima Hilal

This study tests a brain age model on Singaporean children and elderly, finding that brain age gap change relates to future executive function in both groups.

WMH-DualTasker is a weakly-supervised deep learning model that segments white matter hyperintensities and predicts visual ratings, outperforming supervised methods on benchmark datasets.

This paper improves cerebrovascular brain age predictions by harmonizing arterial spin labeling (ASL) features across multiple cohorts using various methods, showing that ASL-specific harmonization enhances model performance.

The paper examines how cerebrovascular disease markers and plasma p-tau181 interact to affect brain connectivity, grey matter volume, and cognitive decline over time.

The paper conducts GWAS on brain volumes, identifies genetic loci, and develops polygenic scores with cross-ancestry predictive ability and causal links to neuropsychiatric disorders.

This study identifies 67 genetic loci associated with head size, finding strong overlaps with cancer pathways and genes, suggesting shared genetic mechanisms between head growth and cancer risk.

This study identifies three novel genetic loci associated with brain arterial diameters through a genome-wide association analysis across diverse populations.

This study performs a meta-analysis of GWAS to identify new genetic loci associated with all-cause and vascular dementia, revealing shared and distinct risk factors.

ExploreASL provides a standardized image processing pipeline for multi-center ASL MRI studies, improving reproducibility and enabling group-level statistical analysis across diverse clinical populations.

The paper identifies 25 genetic loci associated with subcortical brain structure volumes in over 40,000 individuals, revealing novel biology and potential drug targets.

This paper introduces a meta-analytical method that achieves IPD-level results using only aggregate data, enabling robust analysis when individual participant data cannot be shared.