Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

Deep learning methods have achieved significant results in various fields. Due to the
success of these methods, many researchers have used deep learning algorithms in …

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …

Recent critical commentaries unfavorably compare deep learning (DL) with standard
machine learning (SML) approaches for brain imaging data analysis. However, their …

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 …

Alzheimer's Disease (AD) is a brain disorder that causes the brain to shrink and eventually
causes brain cells to die. This neurological condition progressively hampers cognitive and …

Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …

Alzheimer's disease (AD) is the most common neurodegenerative disorder in the elderly.
Early diagnosis of AD plays a vital role in slowing down the progress of AD because there is …

In healthcare, machine learning (ML) shows significant potential to augment patient care,
improve population health, and streamline healthcare workflows. Realizing its full potential …

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 …