Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …

The unprecedented growth of computational capabilities in recent years has allowed
Artificial Intelligence (AI) models to be developed for medical applications with remarkable …

Alzheimer's disease, a primary neurodegenerative condition, predominantly impacts the
elderly and pre-elderly population. This progressive neurological disorder is characterized …

Abstract Information from neuroimaging examinations is increasingly used to support
diagnoses of dementia, eg, Alzheimer's disease. While current clinical practice is mainly …

Abstract Background The field of Alzheimer's disease (AD) diagnosis is undergoing
significant transformation due to the application of deep learning (DL) models. While DL …

FIGURE 2. Progression of electronic large language model (LLM) technology. 1.
Transformer models are probably the basic infrastructure for these technologies (1). 2 …

Clinical adoption of deep learning models has been hindered, in part, because the “black-
box” nature of neural networks leads to concerns regarding their trustworthiness and …

This study extends the application of the frequency-domain new causality method to
functional magnetic resonance imaging analysis. Strong causality, weak causality, balanced …

For decades, a variety of predictive approaches have been proposed and evaluated in terms
of their prediction capability for Alzheimer's Disease (AD) and its precursor–mild cognitive …

Volumetric neuroimaging examinations like structural Magnetic Resonance Imaging (sMRI)
are routinely applied to support the clinical diagnosis of dementia like Alzheimer's Disease …