Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and
clinical observations. However, these diagnoses are not perfect, and additional diagnostic …

Background The improvement of health indicators and life expectancy, especially in
developed countries, has led to population growth and increased age-related diseases …

Deep learning has recently been used for the analysis of neuroimages, such as structural
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …

For significant memory concern (SMC) and mild cognitive impairment (MCI), their
classification performance is limited by confounding features, diverse imaging protocols, and …

Brain connectivity alterations associated with mental disorders have been widely reported in
both functional MRI (fMRI) and diffusion MRI (dMRI). However, extracting useful information …

Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …

Modeling the dynamics characteristics in functional brain networks (FBNs) is important for
understanding the functional mechanism of the human brain. However, the current works do …

Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …

Automated detection of dementia stage using multimodal imaging modalities will be helpful
for improving the clinical diagnosis. In this study, we develop the Inception-ResNet wrapper …

Resting-state functional magnetic resonance imaging (rs-fMRI) data have been widely used
for automated diagnosis of brain disorders such as major depressive disorder (MDD) to …