The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …

With the advances in brain imaging, magnetic resonance imaging (MRI) is evolving as a
popular radiological tool in clinical diagnosis. Deep learning (DL) methods can detect …

In recent years, the discovery of brain effective connectivity (EC) networks through
computational analysis of functional magnetic resonance imaging (fMRI) data has gained …

Using machine learning methods to estimate brain effective connectivity networks from
functional magnetic resonance imaging (fMRI) data has gradually become one of the hot …

Dynamic effective connectivity (DEC) is the accumulation of effective connectivity in the time
dimension, which can describe the continuous neural activities in the brain. Recently …

Using machine learning methods to estimate brain effective connectivity networks from
functional magnetic resonance imaging (fMRI) data has garnered significant attention in the …

Recent advancements in AI, big data analytics, and magnetic resonance imaging (MRI)
have revolutionized the study of brain diseases such as Alzheimer's Disease (AD). However …

Dynamic effective connectivity (DEC) contains abundant temporal and spatial dynamic
information, which can characterize the formation and dissolution of distributed directional …

The study of nicotine addiction mechanism is of great significance in both nicotine
withdrawal and brain science. The detection of addiction-related brain connectivity using …

A wealth of causal relationships exists in biological systems, both causal brain networks and
causal protein signaling networks are very classical causal biological networks (CBNs) …