The functional connectomic profile is one of the non-invasive imaging biomarkers in the
computer-assisted diagnostic system for many neuro-diseases. However, the diagnostic …

Objective: Deep learning (DL) techniques have been introduced to assist doctors in the
interpretation of medical images by detecting image-derived phenotype abnormality. Yet the …

Obsessive-compulsive disorder (OCD) brings many problems to patients. Redundant
information in the OCD data can be removed to preserve valuable biological functions …

Multi-site fMRI studies face the challenge that the pooling introduces systematic non-
biological site-specific variance due to hardware, software, and environment. In this paper …

Since high-order relationships among multiple brain regions-of-interests (ROIs) are helpful
to explore the pathogenesis of neurological diseases more deeply, hypergraph-based brain …

Many supervised machine learning frameworks have been proposed for disease
classification using functional magnetic resonance imaging (fMRI) data, producing important …

Understanding the connection between the brain's structural connectivity and its functional
connectivity is of immense interest in computational neuroscience. Although some studies …

Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at
the individual level, have been limited to date. As diagnostic criteria are currently symptom …

The brain–computer interface (BCI) is a promising technology where a user controls a robot
or computer by thinking with no movement. There are several underlying principles to …

Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is a non-invasive brain
imaging technique that measures brain activity non-invasively. Functional connectivity (FC) …