Biomedical data are becoming increasingly multimodal and thereby capture the underlying
complex relationships among biological processes. Deep learning (DL)-based data fusion …

Advancements in deep learning techniques carry the potential to make significant
contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis …

Digital twin (DT), referring to a promising technique to digitally and accurately represent
actual physical entities, has attracted explosive interests from both academia and industry …

Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and
progression detection have been intensively studied. Nevertheless, research studies often …

Numerous machine learning (ML) approaches have been proposed for automatic
classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 …

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

Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …

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 …

Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort
expended in the interface of medicine and computer science. As some CAD systems in …

Recent advancements in deep learning have led to a resurgence of medical imaging and
Electronic Medical Record (EMR) models for a variety of applications, including clinical …