Md Abdur Rahaman

This paper uses aNy-way ICA to identify a cortico-thalamo-cerebellar circuit in schizophrenia, showing altered connectivity and cognitive impairments across multiple datasets.

SpaDE is a deep learning model for biclustering neuroimaging data that identifies coherent subject and feature subgroups with improved interpretability and performance over existing methods.

This paper introduces a multi-modal AI model for schizophrenia classification using imaging and genetic data, achieving 94.10% accuracy and identifying key brain regions and genes associated with the disorder.

The paper introduces a novel tri-clustering method for dynamic functional network connectivity to identify schizophrenia effects across subgroups in resting fMRI data.

This paper introduces a statelet-based approach to analyze dynamic functional network connectivity, finding reduced modularity and lower connection consistency in schizophrenia patients compared to healthy controls.