Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

The spatio-temporal wind speed prediction technology provides the key technical support for
the energy management and space allocation of the wind farm. To obtain an accurate spatio …

Neurological disorders (NDs), such as Alzheimer's disease, have been a threat to human
health all over the world. It is of great importance to diagnose ND through combining artificial …

Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems
that exhibit human-like intelligence, especially when tackling complex tasks. While the chain …

The multi-modal neuroimage study has provided insights into understanding the
heteromodal relationships between brain network organization and behavioral phenotypes …

The methodology of machine learning with multi-omics data has been widely adopted in the
discriminative analyses of schizophrenia, but most of these studies ignored the cooperative …

Abstract Background and Objective: The accurate diagnosis of schizophrenia spectrum
disorder plays an important role in improving patient outcomes, enabling timely …

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive
neuroimaging technique widely utilized in the research of Autism Spectrum Disorder (ASD) …

Graph theory analysis, as a mathematical tool, has been widely employed in studying the
connectivity of the brain to explore the structural organization. Through the computation of …

Alzheimer's disease (AD) and mild cognitive impairment (MCI) are common cognitive
disorders. Research has shown that cognitive decline is closely related to abnormal …