Yi Hao Chan

This paper introduces BRAINMAP, a model for ADHD diagnosis using dynamic functional connectivity, achieving improved detection with three fMRI datasets.

This paper introduces BrainGAT, a graph neural network for gender classification using multimodal brain connectomes, achieving 83.13% accuracy on the Human Connectome Project dataset.

This paper proposes a method to simplify deep neural networks for decoding brain functional connectomes, achieving similar performance with 2% of the original parameters and identifying relevant biomarkers.

The paper uses deep neural networks to classify brain states in AD, MCI, and CN subjects using fMRI data and identifies salient brain regions associated with these conditions.