Eric J. Barnett

The paper introduces an adversarial neural network to identify genetic resilience markers in Alzheimer's disease, finding five SNPs associated with resilience independent of polygenic risk scores.

This study develops an explainable deep learning model to predict ADHD using genetic, environmental, cognitive, and temperament data, finding that temperament features significantly improve classification performance.

This paper develops a framework using genomic context and genotype data in convolutional neural networks to predict type 2 diabetes risk, showing improved performance over polygenic risk scores.

This study identifies factors affecting model performance in genomic machine learning by analyzing associations between study features and reported results.