With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

Recent years have witnessed a significant advancement in brain imaging techniques that
offer a non-invasive approach to map** the structure and function of the brain …

One of the first signs of Alzheimer's disease (AD) is mild cognitive impairment (MCI), in
which there are small variants of brain changes among the intermediate stages. Although …

Graph Neural Networks (GNNs) have gained momentum in graph representation learning
and boosted the state of the art in a variety of areas, such as data mining (eg, social network …

The diagnosis of early stages of Alzheimer's disease (AD) is essential for timely treatment to
slow further deterioration. Visualizing the morphological features for early stages of AD is of …

As an early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) is able to be
detected by analyzing the brain connectivity networks. For this reason, we devise a new …

Alzheimer's disease (AD) is characterized by alterations of the brain's structural and
functional connectivity during its progressive degenerative processes. Existing auxiliary …

Integrating the brain structural and functional connectivity features is of great significance in
both exploring brain science and analyzing cognitive impairment clinically. However, it …

Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …

Fusing structural-functional images of the brain has shown great potential to analyze the
deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively fuse …