Gayathri Pandey

This study estimates brain age in individuals with alcohol use disorder (AUD) and finds accelerated brain aging associated with impaired neurocognition and impulsivity.

The paper examines neural activity in the reward network during win and loss outcomes in a gambling task and links these activations to behavioral and cognitive traits.

This study uses a multimodal AI approach to identify distinct Alzheimer's subtypes in men and women using MRI, genetic, and clinical data from ADNI.

The paper predicts brain age in individuals with and at risk for alcohol use disorder using morphological brain features and finds accelerated brain aging in both groups.

This study uses machine learning to predict alcohol-related memory problems in older adults by integrating multi-domain features including brain connectivity, polygenic risk, and lifestyle factors.