Background Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic
predementia phase of Alzheimer's disease dementia, characterised by cognitive and …

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

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain
diseases and predicting clinical scores using magnetic resonance imaging (MRI) have …

Early prediction of Alzheimer's disease (AD) is crucial for delaying its progression. As a
chronic disease, ignoring the temporal dimension of AD data affects the performance of a …

We performed this research to 1) evaluate a novel deep learning method for the diagnosis of
Alzheimer's disease (AD) and 2) jointly predict the Mini Mental State Examination (MMSE) …

Many machine learning and pattern classification methods have been applied to the
diagnosis of Alzheimer's disease (AD) and its prodromal stage, ie, mild cognitive impairment …

Alzheimer's disease (AD), the most common form of dementia, shares many aspects of
abnormal brain aging. We present a novel magnetic resonance imaging (MRI)-based …

Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is
important for developing disease-modifying therapies. In this study, given multimodal AD …

The prevalence of Alzheimer's disease (AD) in the growing elderly population makes
accurately predicting AD progression crucial. Due to AD's complex etiology and …

Computational models predicting symptomatic progression at the individual level can be
highly beneficial for early intervention and treatment planning for Alzheimer's disease (AD) …