Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is
believed to be essential to disease management because it enables physicians to initiate …

In Alzheimer's disease (AD) assessment, traditional deep learning approaches have often
employed separate methodologies to handle the diverse modalities of input data …

Structural magnetic resonance imaging (sMRI), which can reflect cerebral atrophy, plays an
important role in the early detection of Alzheimer's disease (AD). However, the information …

Alzheimer's disease (AD) is a terrible and degenerative disease commonly occurring in the
elderly. Early detection can prevent patients from further damage, which is crucial in treating …

Abstract Mild Cognitive Impairment (MCI) is an early stage of memory loss or other cognitive
ability loss in individuals who maintain the ability to independently perform most activities of …

Objective We aimed to develop and validate a novel multimodal framework Hi erarchical M
ulti-task A uxiliary L earning (HiMAL) framework, for predicting cognitive composite functions …

Early recognition of Alzheimer's disease (AD) and its precursor state, mild cognitive
impairment (MCI), is pivotal in interrupting the progression of the disease and providing …

Conventional knowledge graphs (KGs) are composed solely of entities, attributes, and
relationships, which poses challenges for enhancing multimodal knowledge representation …

Deep Learning (DL) is currently transforming health services by significantly improving early
cancer diagnosis, drug discovery, protein–protein interaction analysis, and gene editing …