Martin Henry Plawecki

This study uses EEGViT, a transformer-based model, to classify Alcohol Use Disorder from raw resting-state EEG data, achieving 56% accuracy with sex- and age-stratified results.

The paper develops and validates polygenic scores for substance use disorders across multiple ancestries, finding clinically relevant performance in European and Latinx populations but not in African populations.

The paper examines how genetic variants in the cholinergic system affect theta band event-related oscillations, finding age and sex-dependent variations in these associations.

The paper uses polygenic risk scores from GWAS to assess their association with suicidal thoughts and behaviors in a sample with alcohol use disorders, finding significant contributions from multiple PRS.

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.

This paper uses PheWAS to investigate the phenotypic effects of GABRA2 variant rs279858, finding associations with anxiety-related and behavioral traits linked to alcohol use disorders.