The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …

Recent works have shown that deep neural networks can achieve super-human
performance in a wide range of image classification tasks in the medical imaging domain …

Abstract Diagnosing Alzheimer's Disease (AD) in older people using magnetic resonance
imaging (MRI) is quite hard since it requires the extraction of highly discriminative feature …

Artificial intelligence (AI)-based diagnostic systems provide less error-prone and safer
support to clinicians, enhancing the medical decision-making process. This study presents a …

Alzheimer's disease (AD) poses a substantial public health challenge, demanding accurate
screening and diagnosis. Identifying AD in its early stages, including mild cognitive …

The early and effective diagnosis of Alzheimer's disease (AD) and mild cognitive impairment
(MCI) has received increasing attention in recent years. However, currently available deep …

We present a new model trained on multi-modalities of Positron Emission Tomography
images (PET-AV45 and PET-FDG) for Alzheimer's Disease (AD) diagnosis. Unlike the …

Convolutional neural networks (CNNs) have demonstrated excellent performance for brain
disease classification from MRI data. However, CNNs lack the ability to capture global …

Alzheimer's disease (AD) is an irreversible central nervous degenerative disease, while mild
cognitive impairment (MCI) is a precursor state of AD. Accurate early diagnosis of AD is …

Traffic accidents threaten human lives and impose substantial financial burdens annually.
Accurate estimation of accident fatal crash risk is crucial for enhancing road safety and …